Remove llama.cpp submodule and shift new build to top

.dockerignore

@@ -3,9 +3,7 @@ ollama
 app
 macapp
 dist
-build
 .env
 .cache
 test_data
-.git
-
+llama/build

.gitattributes

@@ -7,18 +7,5 @@ llama/**/*.cuh linguist-vendored
 llama/**/*.m linguist-vendored
 llama/**/*.metal linguist-vendored
 
-ml/backend/**/*.c linguist-vendored
-ml/backend/**/*.h linguist-vendored
-ml/backend/**/*.cpp linguist-vendored
-ml/backend/**/*.hpp linguist-vendored
-ml/backend/**/*.cu linguist-vendored
-ml/backend/**/*.cuh linguist-vendored
-ml/backend/**/*.m linguist-vendored
-ml/backend/**/*.metal linguist-vendored
-ml/backend/**/CMakeLists.txt linguist-vendored
-
-llama/build-info.cpp linguist-generated
-ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.s linguist-generated
-
 * text=auto
 *.go text eol=lf

.github/ISSUE_TEMPLATE/10_bug_report.yml

@@ -9,14 +9,6 @@ body:
       description: What happened? What did you expect to happen?
     validations:
       required: true
-  - type: textarea
-    id: logs
-    attributes:
-      label: Relevant log output
-      description: Please copy and paste any relevant log output. See [Troubleshooting Guide](https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md#how-to-troubleshoot-issues) for details.
-      render: shell
-    validations:
-      required: false
   - type: dropdown
     id: os
     attributes:

.github/workflows/test.yaml

@@ -21,7 +21,7 @@ jobs:
   changes:
     runs-on: ubuntu-latest
     outputs:
-      changed: ${{ steps.changes.outputs.changed }}
+      RUNNERS: ${{ steps.changes.outputs.RUNNERS }}
     steps:
       - uses: actions/checkout@v4
         with:
@@ -29,226 +29,255 @@ jobs:
       - id: changes
         run: |
           changed() {
-            local BASE=${{ github.event.pull_request.base.sha }}
-            local HEAD=${{ github.event.pull_request.head.sha }}
-            local MERGE_BASE=$(git merge-base $BASE $HEAD)
-            git diff-tree -r --no-commit-id --name-only "$MERGE_BASE" "$HEAD" \
+            git diff-tree -r --no-commit-id --name-only \
+              $(git merge-base ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }}) \
+              ${{ github.event.pull_request.head.sha }} \
               | xargs python3 -c "import sys; from pathlib import Path; print(any(Path(x).match(glob) for x in sys.argv[1:] for glob in '$*'.split(' ')))"
           }
 
-          echo changed=$(changed 'llama/llama.cpp/**/*' 'ml/backend/ggml/ggml/**/*') | tee -a $GITHUB_OUTPUT
+          {
+            echo RUNNERS=$(changed 'llama/**')
+          } >>$GITHUB_OUTPUT
 
-  linux:
+  runners-linux-cuda:
     needs: [changes]
-    if: needs.changes.outputs.changed == 'True'
+    if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
     strategy:
       matrix:
-        include:
-          - preset: CPU
-          - preset: CUDA
-            container: nvidia/cuda:13.0.0-devel-ubuntu22.04
-            flags: '-DCMAKE_CUDA_ARCHITECTURES=87'
-          - preset: ROCm
-            container: rocm/dev-ubuntu-22.04:6.1.2
-            extra-packages: rocm-libs
-            flags: '-DAMDGPU_TARGETS=gfx1010 -DCMAKE_PREFIX_PATH=/opt/rocm'
+        cuda-version:
+          - '11.8.0'
     runs-on: linux
-    container: ${{ matrix.container }}
+    container: nvidia/cuda:${{ matrix.cuda-version }}-devel-ubuntu20.04
     steps:
-      - uses: actions/checkout@v4
       - run: |
-          [ -n "${{ matrix.container }}" ] || sudo=sudo
-          $sudo apt-get update
-          $sudo apt-get install -y cmake ccache ${{ matrix.extra-packages }}
+          apt-get update && apt-get install -y git build-essential curl
         env:
           DEBIAN_FRONTEND: noninteractive
-      - uses: actions/cache@v4
+      - uses: actions/checkout@v4
+      - uses: actions/setup-go@v4
         with:
-          path: /github/home/.cache/ccache
-          key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}
+          go-version-file: go.mod
+          cache: true
+      - run: go get ./...
       - run: |
-          cmake --preset ${{ matrix.preset }} ${{ matrix.flags }}
-          cmake --build --preset ${{ matrix.preset }} --parallel
-
-  windows:
+          git config --global --add safe.directory /__w/ollama/ollama
+          cores=$(grep '^core id' /proc/cpuinfo |sort -u|wc -l)
+          make -j $cores cuda_v11
+  runners-linux-rocm:
     needs: [changes]
-    if: needs.changes.outputs.changed == 'True'
+    if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
     strategy:
       matrix:
-        include:
-          - preset: CPU
-          - preset: CUDA
-            install: https://developer.download.nvidia.com/compute/cuda/13.0.0/local_installers/cuda_13.0.0_windows.exe
-            flags: '-DCMAKE_CUDA_ARCHITECTURES=80'
-            cuda-components:
-              - '"cudart"'
-              - '"nvcc"'
-              - '"cublas"'
-              - '"cublas_dev"'
-              - '"crt"'
-              - '"nvvm"'
-              - '"nvptxcompiler"'
-            cuda-version: '13.0'
-          - preset: ROCm
-            install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
-            flags: '-DAMDGPU_TARGETS=gfx1010 -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
+        rocm-version:
+          - '6.1.2'
+    runs-on: linux
+    container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
+    steps:
+      - run: |
+          apt-get update && apt-get install -y git build-essential curl rocm-libs
+        env:
+          DEBIAN_FRONTEND: noninteractive
+      - uses: actions/checkout@v4
+      - uses: actions/setup-go@v4
+        with:
+          go-version-file: go.mod
+          cache: true
+      - run: go get ./...
+      - run: |
+          git config --global --add safe.directory /__w/ollama/ollama
+          cores=$(grep '^core id' /proc/cpuinfo |sort -u|wc -l)
+          make -j $cores rocm
+
+  # ROCm generation step
+  runners-windows-rocm:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
     runs-on: windows
     steps:
-      - run: |
-          choco install -y --no-progress ccache ninja
-          ccache -o cache_dir=${{ github.workspace }}\.ccache
-      - if: matrix.preset == 'CUDA' || matrix.preset == 'ROCm'
-        id: cache-install
-        uses: actions/cache/restore@v4
-        with:
-          path: |
-            C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
-            C:\Program Files\AMD\ROCm
-          key: ${{ matrix.install }}
-      - if: matrix.preset == 'CUDA'
-        name: Install CUDA ${{ matrix.cuda-version }}
-        run: |
-          $ErrorActionPreference = "Stop"
-          if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
-            Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            $subpackages = @(${{ join(matrix.cuda-components, ', ') }}) | Foreach-Object {"${_}_${{ matrix.cuda-version }}"}
-            Start-Process -FilePath .\install.exe -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
-          }
-
-          $cudaPath = (Resolve-Path "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\*").path
-          echo "$cudaPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-      - if: matrix.preset == 'ROCm'
-        name: Install ROCm ${{ matrix.rocm-version }}
-        run: |
-          $ErrorActionPreference = "Stop"
-          if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
-            Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
-            Start-Process -FilePath .\install.exe -ArgumentList '-install' -NoNewWindow -Wait
-          }
-
-          $hipPath = (Resolve-Path "C:\Program Files\AMD\ROCm\*").path
-          echo "$hipPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-          echo "CC=$hipPath\bin\clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "CXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "HIPCXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "HIP_PLATFORM=amd" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "CMAKE_PREFIX_PATH=$hipPath" | Out-File -FilePath $env:GITHUB_ENV -Append
-      - if: ${{ !cancelled() && steps.cache-install.outputs.cache-hit != 'true' }}
-        uses: actions/cache/save@v4
-        with:
-          path: |
-            C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
-            C:\Program Files\AMD\ROCm
-          key: ${{ matrix.install }}
       - uses: actions/checkout@v4
-      - uses: actions/cache@v4
+      - uses: actions/setup-go@v5
         with:
-          path: ${{ github.workspace }}\.ccache
-          key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ matrix.preset }}
+          go-version-file: go.mod
+          cache: true
+      - name: 'Install ROCm'
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading AMD HIP Installer"
+          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
+          write-host "Installing AMD HIP"
+          Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
+          write-host "Completed AMD HIP"
+      - name: 'Verify ROCm'
+        run: |
+          & 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
+      - run: go get ./...
       - run: |
-          Import-Module 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
-          Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
-          cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }}
-          cmake --build --parallel --preset "${{ matrix.preset }}"
-        env:
-          CMAKE_GENERATOR: Ninja
+          $gopath=(get-command go).source | split-path -parent
+          import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
+          Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
+          $env:PATH="$gopath;$env:PATH"
+          $env:OLLAMA_SKIP_CPU_GENERATE="1"
+          $env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
+          $cores = (Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores
+          write-host $env:HIP_PATH
+          make -C llama print-HIP_PATH print-HIP_LIB_DIR
+          make -j $cores rocm
+        name: make
 
-  go_mod_tidy:
-    runs-on: ubuntu-latest
+  # CUDA generation step
+  runners-windows-cuda:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
+    runs-on: windows
     steps:
       - uses: actions/checkout@v4
-      - name: check that 'go mod tidy' is clean
-        run: go mod tidy --diff || (echo "Please run 'go mod tidy'." && exit 1)
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+      - name: 'Install CUDA'
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading CUDA Installer"
+          Invoke-WebRequest -Uri "https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe" -OutFile "${env:RUNNER_TEMP}\cuda-install.exe"
+          write-host "Installing CUDA"
+          Start-Process "${env:RUNNER_TEMP}\cuda-install.exe" -ArgumentList '-s' -NoNewWindow -Wait
+          write-host "Completed CUDA"
+          $cudaPath=((resolve-path "c:\Program Files\NVIDIA*\CUDA\v*\bin\nvcc.exe")[0].path | split-path | split-path)
+          $cudaVer=($cudaPath | split-path -leaf ) -replace 'v(\d+).(\d+)', '$1_$2' 
+          echo "$cudaPath\bin" >> $env:GITHUB_PATH
+          echo "CUDA_PATH=$cudaPath" >> $env:GITHUB_ENV
+          echo "CUDA_PATH_V${cudaVer}=$cudaPath" >> $env:GITHUB_ENV
+          echo "CUDA_PATH_VX_Y=CUDA_PATH_V${cudaVer}" >> $env:GITHUB_ENV
+      - name: 'Verify CUDA'
+        run: nvcc -V
+      - run: go get ./...
+      - name: make
+        run: |
+          $gopath=(get-command go).source | split-path -parent
+          $cudabin=(get-command nvcc).source | split-path
+          import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
+          Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$cudabin;$env:PATH"
+          $env:OLLAMA_SKIP_CPU_GENERATE="1"
+          $cores = (Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores
+          make -j $cores cuda_v11
+        env:
+          OLLAMA_SKIP_CPU_GENERATE: '1'
 
+  runners-cpu:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-2019]
+        arch: [amd64, arm64]
+        exclude:
+          - os: ubuntu-latest
+            arch: arm64
+          - os: windows-2019
+            arch: arm64
+    runs-on: ${{ matrix.os }}
+    env:
+      GOARCH: ${{ matrix.arch }}
+      ARCH: ${{ matrix.arch }}
+      CGO_ENABLED: '1'
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+      - run: go get ./...
+      - name: 'Build Windows Go Runners'
+        if: ${{ startsWith(matrix.os, 'windows-') }}
+        run: |
+          $gopath=(get-command go).source | split-path -parent
+          $gccpath=(get-command gcc).source | split-path -parent
+          import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
+          Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$gccpath;$env:PATH"
+          echo $env:PATH
+          make -j 4      
+      - name: 'Build Unix Go Runners'
+        if: ${{ ! startsWith(matrix.os, 'windows-') }}
+        run: make -j 4
+      - run: go build .
+
+  lint:
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-2019]
+        arch: [amd64, arm64]
+        exclude:
+          - os: ubuntu-latest
+            arch: arm64
+          - os: windows-2019
+            arch: arm64
+          - os: macos-latest
+            arch: amd64
+    runs-on: ${{ matrix.os }}
+    env:
+      GOARCH: ${{ matrix.arch }}
+      CGO_ENABLED: '1'
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: false
+      - run: |
+          case ${{ matrix.arch }} in
+            amd64) echo ARCH=x86_64 ;;
+            arm64) echo ARCH=arm64 ;;
+          esac >>$GITHUB_ENV
+        shell: bash
+      - uses: golangci/golangci-lint-action@v6
+        with:
+          args: --timeout 8m0s -v
   test:
     strategy:
       matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
+        os: [ubuntu-latest, macos-latest, windows-2019]
+        arch: [amd64]
+        exclude:
+          - os: ubuntu-latest
+            arch: arm64
+          - os: windows-2019
+            arch: arm64
     runs-on: ${{ matrix.os }}
     env:
+      GOARCH: ${{ matrix.arch }}
       CGO_ENABLED: '1'
-      GOEXPERIMENT: 'synctest'
     steps:
-      - name: checkout
-        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # 4.2.2
-
-      - name: cache restore
-        uses: actions/cache/restore@1bd1e32a3bdc45362d1e726936510720a7c30a57 # v4.2.0
+      - uses: actions/checkout@v4
         with:
-          # Note: unlike the other setups, this is only grabbing the mod download
-          # cache, rather than the whole mod directory, as the download cache
-          # contains zips that can be unpacked in parallel faster than they can be
-          # fetched and extracted by tar
-          path: |
-            ~/.cache/go-build
-            ~/go/pkg/mod/cache
-            ~\AppData\Local\go-build
-          # NOTE: The -3- here should be incremented when the scheme of data to be
-          # cached changes (e.g. path above changes).
-          key: ${{ github.job }}-${{ runner.os }}-${{ matrix.goarch }}-${{ matrix.buildflags }}-go-3-${{ hashFiles('**/go.sum') }}-${{ github.run_id }}
-          restore-keys: |
-            ${{ github.job }}-${{ runner.os }}-${{ matrix.goarch }}-${{ matrix.buildflags }}-go-3-${{ hashFiles('**/go.sum') }}
-            ${{ github.job }}-${{ runner.os }}-${{ matrix.goarch }}-${{ matrix.buildflags }}-go-3-
-
-      - name: Setup Go
-        uses: actions/setup-go@v5
+          submodules: recursive
+      - uses: actions/setup-go@v5
         with:
-          # The caching strategy of setup-go is less than ideal, and wastes
-          # time by not saving artifacts due to small failures like the linter
-          # complaining, etc. This means subsequent have to rebuild their world
-          # again until all checks pass. For instance, if you mispell a word,
-          # you're punished until you fix it. This is more hostile than
-          # helpful.
-          cache: false
-
           go-version-file: go.mod
-
-      # It is tempting to run this in a platform independent way, but the past
-      # shows this codebase will see introductions of platform specific code
-      # generation, and so we need to check this per platform to ensure we
-      # don't abuse go generate on specific platforms.
-      - name: check that 'go generate' is clean
-        if: always()
-        run: |
-          go generate ./...
-          git diff --name-only --exit-code || (echo "Please run 'go generate ./...'." && exit 1)
-
-      - name: go test
-        if: always()
-        run: go test -count=1 -benchtime=1x ./...
-
-      # TODO(bmizerany): replace this heavy tool with just the
-      # tools/checks/binaries we want and then make them all run in parallel
-      # across jobs, not on a single tiny vm on Github Actions.
-      - uses: golangci/golangci-lint-action@v6
-        with:
-          args: --timeout 10m0s -v
-
-      - name: cache save
-        # Always save the cache, even if the job fails. The artifacts produced
-        # during the building of test binaries are not all for naught. They can
-        # be used to speed up subsequent runs.
-        if: always()
-
-        uses: actions/cache/save@1bd1e32a3bdc45362d1e726936510720a7c30a57 # v4.2.0
-        with:
-          # Note: unlike the other setups, this is only grabbing the mod download
-          # cache, rather than the whole mod directory, as the download cache
-          # contains zips that can be unpacked in parallel faster than they can be
-          # fetched and extracted by tar
-          path: |
-            ~/.cache/go-build
-            ~/go/pkg/mod/cache
-            ~\AppData\Local\go-build
-          # NOTE: The -3- here should be incremented when the scheme of data to be
-          # cached changes (e.g. path above changes).
-          key: ${{ github.job }}-${{ runner.os }}-${{ matrix.goarch }}-${{ matrix.buildflags }}-go-3-${{ hashFiles('**/go.sum') }}-${{ github.run_id }}
+          cache: true
+      - run: |
+          case ${{ matrix.arch }} in
+            amd64) echo ARCH=amd64 ;;
+            arm64) echo ARCH=arm64 ;;
+          esac >>$GITHUB_ENV
+        shell: bash
+      - run: go build
+      - run: go test -v ./...
 
   patches:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - name: Verify patches apply cleanly and do not change files
+        with:
+          submodules: recursive
+      - name: Verify patches carry all the changes
         run: |
-          make -f Makefile.sync clean checkout apply-patches sync
-          git diff --compact-summary --exit-code
+          make apply-patches sync && git diff --compact-summary --exit-code llama

.gitignore

@@ -4,13 +4,15 @@
 .venv
 .swp
 dist
-build
+ollama
 .cache
 *.exe
 .idea
 test_data
 *.crt
-__debug_bin*
+llm/build
+build/*/*/*
+!build/**/placeholder
 llama/build
-llama/vendor
-/ollama
+__debug_bin*
+llama/vendor

.golangci.yaml

@@ -6,6 +6,10 @@ linters:
     - bidichk
     - bodyclose
     - containedctx
+    - contextcheck
+    - errcheck
+    - exportloopref
+    - gci
     - gocheckcompilerdirectives
     - gofmt
     - gofumpt
@@ -19,14 +23,15 @@ linters:
     - nolintlint
     - nosprintfhostport
     - staticcheck
+    - tenv
     - unconvert
-    - usetesting
+    - unused
+    - usestdlibvars
     - wastedassign
     - whitespace
-  disable:
-    - usestdlibvars
-    - errcheck
 linters-settings:
+  gci:
+    sections: [standard, default, localmodule]
   staticcheck:
     checks:
       - all
@@ -38,4 +43,5 @@ severity:
         - gofmt
         - goimports
         - intrange
+        - usestdlibvars
       severity: info

.prettierrc.json

@@ -0,0 +1,10 @@
+{
+  "trailingComma": "es5",
+  "tabWidth": 2,
+  "useTabs": false,
+  "semi": false,
+  "singleQuote": true,
+  "jsxSingleQuote": true,
+  "printWidth": 120,
+  "arrowParens": "avoid"
+}

CMakeLists.txt

@@ -1,139 +0,0 @@
-cmake_minimum_required(VERSION 3.21)
-
-project(Ollama C CXX)
-
-include(CheckLanguage)
-include(GNUInstallDirs)
-
-find_package(Threads REQUIRED)
-
-set(CMAKE_BUILD_TYPE Release)
-set(BUILD_SHARED_LIBS ON)
-
-set(CMAKE_CXX_STANDARD 17)
-set(CMAKE_CXX_STANDARD_REQUIRED ON)
-set(CMAKE_CXX_EXTENSIONS OFF)
-
-set(GGML_BUILD ON)
-set(GGML_SHARED ON)
-set(GGML_CCACHE ON)
-set(GGML_BACKEND_DL ON)
-set(GGML_BACKEND_SHARED ON)
-set(GGML_SCHED_MAX_COPIES 4)
-
-set(GGML_LLAMAFILE ON)
-set(GGML_CUDA_PEER_MAX_BATCH_SIZE 128)
-set(GGML_CUDA_GRAPHS ON)
-set(GGML_CUDA_FA ON)
-set(GGML_CUDA_COMPRESSION_MODE default)
-
-if((CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_OSX_ARCHITECTURES MATCHES "arm64")
-    OR (NOT CMAKE_OSX_ARCHITECTURES AND NOT CMAKE_SYSTEM_PROCESSOR MATCHES "arm|aarch64|ARM64|ARMv[0-9]+"))
-    set(GGML_CPU_ALL_VARIANTS ON)
-endif()
-
-if (CMAKE_OSX_ARCHITECTURES MATCHES "x86_64")
-    set(CMAKE_BUILD_RPATH "@loader_path")
-    set(CMAKE_INSTALL_RPATH "@loader_path")
-endif()
-
-set(OLLAMA_BUILD_DIR ${CMAKE_BINARY_DIR}/lib/ollama)
-set(OLLAMA_INSTALL_DIR ${CMAKE_INSTALL_PREFIX}/lib/ollama/${OLLAMA_RUNNER_DIR})
-
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY         ${OLLAMA_BUILD_DIR})
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_DEBUG   ${OLLAMA_BUILD_DIR})
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY_RELEASE ${OLLAMA_BUILD_DIR})
-set(CMAKE_LIBRARY_OUTPUT_DIRECTORY         ${OLLAMA_BUILD_DIR})
-set(CMAKE_LIBRARY_OUTPUT_DIRECTORY_DEBUG   ${OLLAMA_BUILD_DIR})
-set(CMAKE_LIBRARY_OUTPUT_DIRECTORY_RELEASE ${OLLAMA_BUILD_DIR})
-
-include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
-include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/include)
-include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu)
-include_directories(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu/amx)
-
-add_compile_definitions(NDEBUG GGML_VERSION=0x0 GGML_COMMIT=0x0)
-
-set(GGML_CPU ON)
-add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src)
-set_property(TARGET ggml PROPERTY EXCLUDE_FROM_ALL TRUE)
-
-get_target_property(CPU_VARIANTS ggml-cpu MANUALLY_ADDED_DEPENDENCIES)
-if(NOT CPU_VARIANTS)
-    set(CPU_VARIANTS "ggml-cpu")
-endif()
-
-install(TARGETS ggml-base ${CPU_VARIANTS}
-    RUNTIME_DEPENDENCIES
-        PRE_EXCLUDE_REGEXES ".*"
-    RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CPU
-    LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CPU
-    FRAMEWORK DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CPU
-)
-
-check_language(CUDA)
-if(CMAKE_CUDA_COMPILER)
-    if(CMAKE_VERSION VERSION_GREATER_EQUAL "3.24" AND NOT CMAKE_CUDA_ARCHITECTURES)
-        set(CMAKE_CUDA_ARCHITECTURES "native")
-    endif()
-
-    find_package(CUDAToolkit)
-    add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cuda)
-    install(TARGETS ggml-cuda
-        RUNTIME_DEPENDENCIES
-            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_BIN_DIR}/x64 ${CUDAToolkit_LIBRARY_DIR}
-            PRE_INCLUDE_REGEXES cublas cublasLt cudart
-            PRE_EXCLUDE_REGEXES ".*"
-        RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA
-        LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT CUDA
-    )
-endif()
-
-set(WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX "^gfx(906|908|90a|1200|1201):xnack[+-]$"
-    CACHE STRING
-    "Regular expression describing AMDGPU_TARGETS not supported on Windows. Override to force building these targets. Default \"^gfx(906|908|90a|1200|1201):xnack[+-]$\"."
-)
-
-check_language(HIP)
-if(CMAKE_HIP_COMPILER)
-    set(HIP_PLATFORM "amd")
-
-    find_package(hip REQUIRED)
-    if(NOT AMDGPU_TARGETS)
-        list(FILTER AMDGPU_TARGETS INCLUDE REGEX "^gfx(900|94[012]|101[02]|1030|110[012]|120[01])$")
-    elseif(WIN32 AND WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX)
-        list(FILTER AMDGPU_TARGETS EXCLUDE REGEX ${WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX})
-    endif()
-
-    if(AMDGPU_TARGETS)
-        add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-hip)
-
-        if (WIN32)
-            target_compile_definitions(ggml-hip PRIVATE GGML_CUDA_NO_PEER_COPY)
-        endif()
-
-        target_compile_definitions(ggml-hip PRIVATE GGML_HIP_NO_VMM)
-
-        set(OLLAMA_HIP_INSTALL_DIR ${OLLAMA_INSTALL_DIR}/rocm)
-        install(TARGETS ggml-hip
-            RUNTIME_DEPENDENCY_SET rocm
-            RUNTIME DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
-            LIBRARY DESTINATION ${OLLAMA_INSTALL_DIR} COMPONENT HIP
-        )
-        install(RUNTIME_DEPENDENCY_SET rocm
-                DIRECTORIES ${HIP_BIN_INSTALL_DIR} ${HIP_LIB_INSTALL_DIR}
-                PRE_INCLUDE_REGEXES hipblas rocblas amdhip64 rocsolver amd_comgr hsa-runtime64 rocsparse tinfo rocprofiler-register drm drm_amdgpu numa elf
-                PRE_EXCLUDE_REGEXES ".*"
-                POST_EXCLUDE_REGEXES "system32"
-            RUNTIME DESTINATION ${OLLAMA_HIP_INSTALL_DIR} COMPONENT HIP
-            LIBRARY DESTINATION ${OLLAMA_HIP_INSTALL_DIR} COMPONENT HIP
-        )
-
-        foreach(HIP_LIB_BIN_INSTALL_DIR IN ITEMS ${HIP_BIN_INSTALL_DIR} ${HIP_LIB_INSTALL_DIR})
-            if(EXISTS ${HIP_LIB_BIN_INSTALL_DIR}/rocblas)
-                install(DIRECTORY ${HIP_LIB_BIN_INSTALL_DIR}/rocblas DESTINATION ${OLLAMA_HIP_INSTALL_DIR} COMPONENT HIP)
-                break()
-            endif()
-        endforeach()
-    endif()
-endif()

CMakePresets.json

@@ -1,127 +0,0 @@
-{
-  "version": 3,
-  "configurePresets": [
-    {
-      "name": "Default",
-      "binaryDir": "${sourceDir}/build",
-      "installDir": "${sourceDir}/dist",
-      "cacheVariables": {
-        "CMAKE_BUILD_TYPE": "Release",
-        "CMAKE_MSVC_RUNTIME_LIBRARY": "MultiThreaded"
-      }
-    },
-    {
-      "name": "CPU",
-      "inherits": [ "Default" ]
-    },
-    {
-      "name": "CUDA",
-      "inherits": [ "Default" ]
-    },
-    {
-      "name": "CUDA 11",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "50-virtual;60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual",
-        "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2"
-      }
-    },
-    {
-      "name": "CUDA 12",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "50;60;61;70;75;80;86;87;89;90;90a;120",
-        "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2"
-      }
-    },
-    {
-      "name": "CUDA 13",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "75-virtual;80-virtual;86-virtual;87-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;110-virtual;120-virtual;121-virtual",
-        "CMAKE_CUDA_FLAGS": "-t 2"
-      }
-    },
-    {
-      "name": "JetPack 5",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "72;87"
-      }
-    },
-    {
-      "name": "JetPack 6",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "87"
-      }
-    },
-    {
-      "name": "ROCm",
-      "inherits": [ "Default" ],
-      "cacheVariables": {
-        "CMAKE_HIP_PLATFORM": "amd"
-      }
-    },
-    {
-      "name": "ROCm 6",
-      "inherits": [ "ROCm" ],
-      "cacheVariables": {
-        "CMAKE_HIP_FLAGS": "-parallel-jobs=4",
-        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx1200;gfx1201;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
-      }
-    }
-  ],
-  "buildPresets": [
-    {
-      "name": "Default",
-      "configurePreset": "Default",
-      "configuration": "Release"
-    },
-    {
-      "name": "CPU",
-      "configurePreset": "Default",
-      "targets": [ "ggml-cpu" ]
-    },
-    {
-      "name": "CUDA",
-      "configurePreset": "CUDA",
-      "targets": [ "ggml-cuda" ]
-    },
-    {
-      "name": "CUDA 11",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "CUDA 11"
-    },
-    {
-      "name": "CUDA 12",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "CUDA 12"
-    },
-    {
-      "name": "CUDA 13",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "CUDA 13"
-    },
-    {
-      "name": "JetPack 5",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "JetPack 5"
-    },
-    {
-      "name": "JetPack 6",
-      "inherits": [ "CUDA" ],
-      "configurePreset": "JetPack 6"
-    },
-    {
-      "name": "ROCm",
-      "configurePreset": "ROCm",
-      "targets": [ "ggml-hip" ]
-    },
-    {
-      "name": "ROCm 6",
-      "inherits": [ "ROCm" ],
-      "configurePreset": "ROCm 6"
-    }
-  ]
-}

CONTRIBUTING.md

@@ -6,6 +6,8 @@ Thank you for your interest in contributing to Ollama! Here are a few guidelines
 
 See the [development documentation](./docs/development.md) for instructions on how to build and run Ollama locally.
 
+## Pull requests
+
 ### Ideal issues
 
 * [Bugs](https://github.com/ollama/ollama/issues?q=is%3Aissue+is%3Aopen+label%3Abug): issues where Ollama stops working or where it results in an unexpected error.
@@ -24,65 +26,11 @@ See the [development documentation](./docs/development.md) for instructions on h
 * Changes that add significant friction to the user experience
 * Changes that create a large future maintenance burden for maintainers and contributors
 
-## Proposing a (non-trivial) change
+### Best practices
 
-> By "non-trivial", we mean a change that is not a bug fix or small
-> documentation update. If you are unsure, please ask us on our [Discord
-> server](https://discord.gg/ollama).
-
-Before opening a non-trivial Pull Request, please open an issue to discuss the change and
-get feedback from the maintainers. This helps us understand the context of the
-change and how it fits into Ollama's roadmap and prevents us from duplicating
-work or you from spending time on a change that we may not be able to accept.
-
-Tips for proposals:
-
-* Explain the problem you are trying to solve, not what you are trying to do.
-* Explain why the change is important.
-* Explain how the change will be used.
-* Explain how the change will be tested.
-
-Additionally, for bonus points: Provide draft documentation you would expect to
-see if the change were accepted.
-
-## Pull requests
-
-**Commit messages**
-
-The title should look like:
-
-    <package>: <short description>
-
-The package is the most affected Go package. If the change does not affect Go
-code, then use the directory name instead. Changes to a single well-known
-file in the root directory may use the file name.
-
-The short description should start with a lowercase letter and be a
-continuation of the sentence:
-
-      "This changes Ollama to..."
-
-Examples:
-
-      llm/backend/mlx: support the llama architecture
-      CONTRIBUTING: provide clarity on good commit messages, and bad
-      docs: simplify manual installation with shorter curl commands
-
-Bad Examples:
-
-      feat: add more emoji
-      fix: was not using famous web framework
-      chore: generify code
-
-**Tests**
-
-Please include tests. Strive to test behavior, not implementation.
-
-**New dependencies**
-
-Dependencies should be added sparingly. If you are adding a new dependency,
-please explain why it is necessary and what other ways you attempted that
-did not work without it.
+* Commit messages: please leave both a title and a description in your commit messages. The title should be a short summary of the changes, with a leading word that explains the section of the code being changed (e.g. `api: fix parsing of prompt field`) . In the description, leave a short 2-3 sentences that explain more about the change and its impact.
+* Tests: please add test coverage to changes where possible.
+* Minimize dependencies: avoid adding new dependencies unless absolutely necessary.
 
 ## Need help?
 

Dockerfile

@@ -1,147 +1,221 @@
-# vim: filetype=dockerfile
+# Note: once we have fully transitioned to the Go server, this will replace the old Dockerfile at the top of the tree
+ARG GOLANG_VERSION=1.22.5
+ARG CMAKE_VERSION=3.22.1
+ARG CUDA_VERSION_11=11.3.1
+ARG CUDA_V11_ARCHITECTURES="50;52;53;60;61;62;70;72;75;80;86"
+ARG CUDA_VERSION_12=12.4.0
+ARG CUDA_V12_ARCHITECTURES="60;61;62;70;72;75;80;86;87;89;90;90a"
+ARG ROCM_VERSION=6.1.2
 
-ARG FLAVOR=${TARGETARCH}
+### To create a local image for building linux binaries on mac or windows with efficient incremental builds
+#
+# docker build --platform linux/amd64 -t builder-amd64 -f Dockerfile --target unified-builder-amd64 .
+# docker run --platform linux/amd64 --rm -it -v $(pwd):/go/src/github.com/ollama/ollama/ builder-amd64
+#
+### Then incremental builds will be much faster in this container
+#
+# make -C llama -j 10 && go build -trimpath -o dist/linux-amd64/ollama .
+#
+FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS unified-builder-amd64
+ARG CMAKE_VERSION
+ARG GOLANG_VERSION
+ARG CUDA_VERSION_11
+ARG CUDA_VERSION_12
+COPY ./scripts/rh_linux_deps.sh /
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:/usr/local/cuda/bin:$PATH
+ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64
+ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:/opt/amdgpu/lib64
+RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
+RUN yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo && \
+    dnf clean all && \
+    dnf install -y \
+    zsh \
+    cuda-$(echo ${CUDA_VERSION_11} | cut -f1-2 -d. | sed -e "s/\./-/g") \
+    cuda-$(echo ${CUDA_VERSION_12} | cut -f1-2 -d. | sed -e "s/\./-/g")
+# TODO intel oneapi goes here...
+ENV GOARCH amd64
+ENV CGO_ENABLED 1
+WORKDIR /go/src/github.com/ollama/ollama/
+ENTRYPOINT [ "zsh" ]
 
-ARG ROCMVERSION=6.3.3
-ARG JETPACK5VERSION=r35.4.1
-ARG JETPACK6VERSION=r36.4.0
-ARG CMAKEVERSION=3.31.2
+### To create a local image for building linux binaries on mac or linux/arm64 with efficient incremental builds
+# Note: this does not contain jetson variants
+#
+# docker build --platform linux/arm64 -t builder-arm64 -f Dockerfile --target unified-builder-arm64 .
+# docker run --platform linux/arm64 --rm -it -v $(pwd):/go/src/github.com/ollama/ollama/ builder-arm64
+#
+FROM --platform=linux/arm64 rockylinux:8 AS unified-builder-arm64
+ARG CMAKE_VERSION
+ARG GOLANG_VERSION
+ARG CUDA_VERSION_11
+ARG CUDA_VERSION_12
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
+RUN yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo && \
+    dnf config-manager --set-enabled appstream && \
+    dnf clean all && \
+    dnf install -y \
+    zsh \
+    cuda-toolkit-$(echo ${CUDA_VERSION_11} | cut -f1-2 -d. | sed -e "s/\./-/g") \
+    cuda-toolkit-$(echo ${CUDA_VERSION_12} | cut -f1-2 -d. | sed -e "s/\./-/g")
+ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH:/usr/local/cuda/bin
+ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64
+ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:/opt/amdgpu/lib64
+ENV GOARCH amd64
+ENV CGO_ENABLED 1
+WORKDIR /go/src/github.com/ollama/ollama/
+ENTRYPOINT [ "zsh" ]
 
-# We require gcc v10 minimum.  v10.3 has regressions, so the rockylinux 8.5 AppStream has the latest compatible version
-FROM --platform=linux/amd64 rocm/dev-almalinux-8:${ROCMVERSION}-complete AS base-amd64
-RUN yum install -y yum-utils \
-    && yum-config-manager --add-repo https://dl.rockylinux.org/vault/rocky/8.5/AppStream/\$basearch/os/ \
-    && rpm --import https://dl.rockylinux.org/pub/rocky/RPM-GPG-KEY-Rocky-8 \
-    && dnf install -y yum-utils ccache gcc-toolset-10-gcc-10.2.1-8.2.el8 gcc-toolset-10-gcc-c++-10.2.1-8.2.el8 gcc-toolset-10-binutils-2.35-11.el8 \
-    && dnf install -y ccache \
-    && yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
-ENV PATH=/opt/rh/gcc-toolset-10/root/usr/bin:$PATH
-
-FROM --platform=linux/arm64 almalinux:8 AS base-arm64
-# install epel-release for ccache
-RUN yum install -y yum-utils epel-release \
-    && dnf install -y clang ccache \
-    && yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo
-ENV CC=clang CXX=clang++
-
-FROM base-${TARGETARCH} AS base
-ARG CMAKEVERSION
-RUN curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
-COPY CMakeLists.txt CMakePresets.json .
-COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-ENV LDFLAGS=-s
-
-FROM base AS cpu
-RUN dnf install -y gcc-toolset-11-gcc gcc-toolset-11-gcc-c++
-ENV PATH=/opt/rh/gcc-toolset-11/root/usr/bin:$PATH
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CPU' \
-        && cmake --build --parallel --preset 'CPU' \
-        && cmake --install build --component CPU --strip --parallel 8
-
-FROM base AS cuda-11
-ARG CUDA11VERSION=11.8
-RUN dnf install -y cuda-toolkit-${CUDA11VERSION//./-}
-ENV PATH=/usr/local/cuda-11/bin:$PATH
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 11' -DOLLAMA_RUNNER_DIR="cuda_v11" \
-        && cmake --build --parallel --preset 'CUDA 11' \
-        && cmake --install build --component CUDA --strip --parallel 8
-
-FROM base AS cuda-12
-ARG CUDA12VERSION=12.8
-RUN dnf install -y cuda-toolkit-${CUDA12VERSION//./-}
-ENV PATH=/usr/local/cuda-12/bin:$PATH
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 12' -DOLLAMA_RUNNER_DIR="cuda_v12"\
-        && cmake --build --parallel --preset 'CUDA 12' \
-        && cmake --install build --component CUDA --strip --parallel 8
-
-
-FROM base AS cuda-13
-ARG CUDA13VERSION=13.0
-RUN dnf install -y cuda-toolkit-${CUDA13VERSION//./-}
-ENV PATH=/usr/local/cuda-13/bin:$PATH
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CUDA 13' -DOLLAMA_RUNNER_DIR="cuda_v13" \
-        && cmake --build --parallel --preset 'CUDA 13' \
-        && cmake --install build --component CUDA --strip --parallel 8
-
-
-FROM base AS rocm-6
-ENV PATH=/opt/rocm/hcc/bin:/opt/rocm/hip/bin:/opt/rocm/bin:/opt/rocm/hcc/bin:$PATH
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'ROCm 6' \
-        && cmake --build --parallel --preset 'ROCm 6' \
-        && cmake --install build --component HIP --strip --parallel 8
-
-FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK5VERSION} AS jetpack-5
-ARG CMAKEVERSION
-RUN apt-get update && apt-get install -y curl ccache \
-    && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
-COPY CMakeLists.txt CMakePresets.json .
-COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'JetPack 5' \
-        && cmake --build --parallel --preset 'JetPack 5' \
-        && cmake --install build --component CUDA --strip --parallel 8
-
-FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK6VERSION} AS jetpack-6
-ARG CMAKEVERSION
-RUN apt-get update && apt-get install -y curl ccache \
-    && curl -fsSL https://github.com/Kitware/CMake/releases/download/v${CMAKEVERSION}/cmake-${CMAKEVERSION}-linux-$(uname -m).tar.gz | tar xz -C /usr/local --strip-components 1
-COPY CMakeLists.txt CMakePresets.json .
-COPY ml/backend/ggml/ggml ml/backend/ggml/ggml
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'JetPack 6' \
-        && cmake --build --parallel --preset 'JetPack 6' \
-        && cmake --install build --component CUDA --strip --parallel 8
-
-FROM base AS build
-WORKDIR /go/src/github.com/ollama/ollama
-COPY go.mod go.sum .
-RUN curl -fsSL https://golang.org/dl/go$(awk '/^go/ { print $2 }' go.mod).linux-$(case $(uname -m) in x86_64) echo amd64 ;; aarch64) echo arm64 ;; esac).tar.gz | tar xz -C /usr/local
-ENV PATH=/usr/local/go/bin:$PATH
-RUN go mod download
+FROM --platform=linux/amd64 unified-builder-amd64 AS runners-amd64
 COPY . .
-ARG GOFLAGS="'-ldflags=-w -s'"
-ENV CGO_ENABLED=1
+ARG OLLAMA_SKIP_CUDA_GENERATE
+ARG OLLAMA_SKIP_CUDA_11_GENERATE
+ARG OLLAMA_SKIP_CUDA_12_GENERATE
+ARG OLLAMA_SKIP_ROCM_GENERATE
+ARG CUDA_V11_ARCHITECTURES
+ARG CUDA_V12_ARCHITECTURES
+ARG OLLAMA_FAST_BUILD
+RUN --mount=type=cache,target=/root/.ccache \
+    if grep "^flags" /proc/cpuinfo|grep avx>/dev/null; then \
+        make -C llama -j $(expr $(nproc) / 2 ) ; \
+    else \
+        make -C llama -j 5 ; \
+    fi
+
+FROM --platform=linux/arm64 unified-builder-arm64 AS runners-arm64
+COPY . .
+ARG OLLAMA_SKIP_CUDA_GENERATE
+ARG OLLAMA_SKIP_CUDA_11_GENERATE
+ARG OLLAMA_SKIP_CUDA_12_GENERATE
+ARG CUDA_V11_ARCHITECTURES
+ARG CUDA_V12_ARCHITECTURES
+ARG OLLAMA_FAST_BUILD
+RUN --mount=type=cache,target=/root/.ccache \
+    make -C llama -j 8
+
+
+# Intermediate stages used for ./scripts/build_linux.sh
+FROM --platform=linux/amd64 centos:7 AS builder-amd64
+ARG CMAKE_VERSION
+ARG GOLANG_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+ENV CGO_ENABLED 1
+ENV GOARCH amd64
+WORKDIR /go/src/github.com/ollama/ollama
+
+FROM --platform=linux/amd64 builder-amd64 AS build-amd64
+COPY . .
+COPY --from=runners-amd64 /go/src/github.com/ollama/ollama/dist/ dist/
+COPY --from=runners-amd64 /go/src/github.com/ollama/ollama/build/ build/
+ARG GOFLAGS
 ARG CGO_CFLAGS
-ARG CGO_CXXFLAGS
-RUN --mount=type=cache,target=/root/.cache/go-build \
-    go build -trimpath -buildmode=pie -o /bin/ollama .
+ARG OLLAMA_SKIP_ROCM_GENERATE
+RUN --mount=type=cache,target=/root/.ccache \
+    go build -trimpath -o dist/linux-amd64/bin/ollama .
+RUN cd dist/linux-$GOARCH && \
+    tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH.tgz
+RUN if [ -z ${OLLAMA_SKIP_ROCM_GENERATE} ] ; then \
+    cd dist/linux-$GOARCH-rocm && \
+    tar -cf - . | pigz --best > ../ollama-linux-$GOARCH-rocm.tgz ;\
+    fi
 
-FROM --platform=linux/amd64 scratch AS amd64
-# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
-COPY --from=cuda-13 dist/lib/ollama/ /lib/ollama/
+FROM --platform=linux/arm64 rockylinux:8 AS builder-arm64
+ARG CMAKE_VERSION
+ARG GOLANG_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
+ENV CGO_ENABLED 1
+ENV GOARCH arm64
+WORKDIR /go/src/github.com/ollama/ollama
 
-FROM --platform=linux/arm64 scratch AS arm64
-# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
-COPY --from=cuda-13 dist/lib/ollama/ /lib/ollama/
-COPY --from=jetpack-5 dist/lib/ollama /lib/ollama/cuda_jetpack5
-COPY --from=jetpack-6 dist/lib/ollama /lib/ollama/cuda_jetpack6
+FROM --platform=linux/arm64 builder-arm64 AS build-arm64
+COPY . .
+COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
+COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/build/ build/
+ARG GOFLAGS
+ARG CGO_CFLAGS
+RUN --mount=type=cache,target=/root/.ccache \
+    go build -trimpath -o dist/linux-arm64/bin/ollama .
+RUN cd dist/linux-$GOARCH && \
+    tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH.tgz
 
-FROM scratch AS rocm
-COPY --from=rocm-6 dist/lib/ollama /lib/ollama
+FROM --platform=linux/amd64 scratch AS dist-amd64
+COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/ollama-linux-*.tgz /
+FROM --platform=linux/arm64 scratch AS dist-arm64
+COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/ollama-linux-*.tgz /
+FROM dist-$TARGETARCH AS dist
 
-FROM ${FLAVOR} AS archive
-COPY --from=cpu dist/lib/ollama /lib/ollama
-COPY --from=build /bin/ollama /bin/ollama
 
-FROM ubuntu:24.04
-RUN apt-get update \
-    && apt-get install -y ca-certificates \
-    && apt-get clean \
-    && rm -rf /var/lib/apt/lists/*
-COPY --from=archive /bin /usr/bin
+# Optimized container images do not cary nested payloads
+FROM --platform=linux/amd64 builder-amd64 AS container-build-amd64
+WORKDIR /go/src/github.com/ollama/ollama
+COPY . .
+ARG GOFLAGS
+ARG CGO_CFLAGS
+RUN --mount=type=cache,target=/root/.ccache \
+    go build -trimpath -o dist/linux-amd64/bin/ollama .
+
+FROM --platform=linux/arm64 builder-arm64 AS container-build-arm64
+WORKDIR /go/src/github.com/ollama/ollama
+COPY . .
+ARG GOFLAGS
+ARG CGO_CFLAGS
+RUN --mount=type=cache,target=/root/.ccache \
+    go build -trimpath -o dist/linux-arm64/bin/ollama .
+
+# For amd64 container images, filter out cuda/rocm to minimize size
+FROM runners-amd64 AS runners-cuda-amd64
+RUN rm -rf \
+    ./dist/linux-amd64/lib/ollama/libggml_hipblas.so \
+    ./dist/linux-amd64/lib/ollama/runners/rocm*
+
+FROM runners-amd64 AS runners-rocm-amd64
+RUN rm -rf \
+    ./dist/linux-amd64/lib/ollama/libggml_cuda*.so \
+    ./dist/linux-amd64/lib/ollama/libcu*.so* \
+    ./dist/linux-amd64/lib/ollama/runners/cuda*
+
+FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-amd64
+RUN apt-get update && \
+    apt-get install -y ca-certificates && \
+    rm -rf /var/lib/apt/lists/*
+COPY --from=container-build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
+COPY --from=runners-cuda-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
+
+FROM --platform=linux/arm64 ubuntu:22.04 AS runtime-arm64
+RUN apt-get update && \
+    apt-get install -y ca-certificates && \
+    rm -rf /var/lib/apt/lists/*
+COPY --from=container-build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/bin/ /bin/
+COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
+
+# ROCm libraries larger so we keep it distinct from the CPU/CUDA image
+FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-rocm
+# Frontload the rocm libraries which are large, and rarely change to increase chance of a common layer
+# across releases
+COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64-rocm/lib/ /lib/
+RUN apt-get update && \
+    apt-get install -y ca-certificates && \
+    rm -rf /var/lib/apt/lists/*
+COPY --from=container-build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
+COPY --from=runners-rocm-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
+
+EXPOSE 11434
+ENV OLLAMA_HOST 0.0.0.0
+
+ENTRYPOINT ["/bin/ollama"]
+CMD ["serve"]
+
+FROM runtime-$TARGETARCH
+EXPOSE 11434
+ENV OLLAMA_HOST 0.0.0.0
 ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
-COPY --from=archive /lib/ollama /usr/lib/ollama
 ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
 ENV NVIDIA_VISIBLE_DEVICES=all
-ENV OLLAMA_HOST=0.0.0.0:11434
-EXPOSE 11434
+
 ENTRYPOINT ["/bin/ollama"]
 CMD ["serve"]

Makefile

@@ -0,0 +1,4 @@
+GOALS := $(or $(MAKECMDGOALS),all)
+.PHONY: $(GOALS)
+$(GOALS):
+	$(MAKE) -C llama $@

Makefile.sync

@@ -1,72 +0,0 @@
-UPSTREAM=https://github.com/ggml-org/llama.cpp.git
-WORKDIR=llama/vendor
-FETCH_HEAD=e54d41befcc1575f4c898c5ff4ef43970cead75f
-
-.PHONY: help
-help:
-	@echo "Available targets:"
-	@echo "    sync                 Sync with upstream repositories"
-	@echo "    checkout             Checkout upstream repository"
-	@echo "    apply-patches        Apply patches to local repository"
-	@echo "    format-patches       Format patches from local repository"
-	@echo "    clean                Clean local repository"
-	@echo
-	@echo "Example:"
-	@echo "    make -f $(lastword $(MAKEFILE_LIST)) clean apply-patches sync"
-
-.PHONY: sync
-sync: llama/build-info.cpp ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal
-
-llama/build-info.cpp: llama/build-info.cpp.in llama/llama.cpp
-	sed -e 's|@FETCH_HEAD@|$(FETCH_HEAD)|' <$< >$@
-
-ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal: ml/backend/ggml/ggml
-	go generate ./$(@D)
-
-.PHONY: llama/llama.cpp
-llama/llama.cpp: llama/vendor
-	rsync -arvzc --delete -f "include LICENSE" -f "merge $@/.rsync-filter" $(addprefix $<,/LICENSE /) $@
-
-.PHONY: ml/backend/ggml/ggml
-ml/backend/ggml/ggml: llama/vendor
-	rsync -arvzc --delete -f "include LICENSE" -f "merge $@/.rsync-filter" $(addprefix $<,/LICENSE /ggml/) $@
-
-PATCHES=$(wildcard llama/patches/*.patch)
-PATCHED=$(join $(dir $(PATCHES)), $(addsuffix ed, $(addprefix ., $(notdir $(PATCHES)))))
-
-.PHONY: apply-patches
-.NOTPARALLEL:
-apply-patches: $(PATCHED)
-
-llama/patches/.%.patched: llama/patches/%.patch
-	@if git -c user.name=nobody -c 'user.email=<>' -C $(WORKDIR) am -3 $(realpath $<); then \
-		touch $@;                                                                           \
-	else                                                                                    \
-		echo "Patch failed. Resolve any conflicts then continue.";                          \
-		echo "1. Run 'git -C $(WORKDIR) am --continue'";                                    \
-		echo "2. Run 'make -f $(lastword $(MAKEFILE_LIST)) format-patches'";                \
-		echo "3. Run 'make -f $(lastword $(MAKEFILE_LIST)) clean apply-patches'";           \
-		exit 1;                                                                             \
-	fi
-
-.PHONY: checkout
-checkout: $(WORKDIR)
-	git -C $(WORKDIR) fetch
-	git -C $(WORKDIR) checkout -f $(FETCH_HEAD)
-
-$(WORKDIR):
-	git clone $(UPSTREAM) $(WORKDIR)
-
-.PHONE: format-patches
-format-patches: llama/patches
-	git -C $(WORKDIR) format-patch \
-		--no-signature \
-		--no-numbered \
-		--zero-commit \
-		-o $(realpath $<) \
-		$(FETCH_HEAD)
-
-.PHONE: clean
-clean: checkout
-	@git -C $(WORKDIR) am --abort || true
-	$(RM) llama/patches/.*.patched

README.md

@@ -1,24 +1,24 @@
 <div align="center">
-  <a href="https://ollama.com">
-    <img alt="ollama" width="240" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
-  </a>
+ <img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
 </div>
 
 # Ollama
 
+[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
+
 Get up and running with large language models.
 
 ### macOS
 
-[Download](https://ollama.com/download/Ollama.dmg)
+[Download](https://ollama.com/download/Ollama-darwin.zip)
 
-### Windows
+### Windows preview
 
 [Download](https://ollama.com/download/OllamaSetup.exe)
 
 ### Linux
 
-```shell
+```
 curl -fsSL https://ollama.com/install.sh | sh
 ```
 
@@ -33,17 +33,12 @@ The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `olla
 - [ollama-python](https://github.com/ollama/ollama-python)
 - [ollama-js](https://github.com/ollama/ollama-js)
 
-### Community
-
-- [Discord](https://discord.gg/ollama)
-- [Reddit](https://reddit.com/r/ollama)
-
 ## Quickstart
 
-To run and chat with [Gemma 3](https://ollama.com/library/gemma3):
+To run and chat with [Llama 3.2](https://ollama.com/library/llama3.2):
 
-```shell
-ollama run gemma3
+```
+ollama run llama3.2
 ```
 
 ## Model library
@@ -52,34 +47,26 @@ Ollama supports a list of models available on [ollama.com/library](https://ollam
 
 Here are some example models that can be downloaded:
 
-| Model              | Parameters | Size  | Download                         |
-| ------------------ | ---------- | ----- | -------------------------------- |
-| Gemma 3            | 1B         | 815MB | `ollama run gemma3:1b`           |
-| Gemma 3            | 4B         | 3.3GB | `ollama run gemma3`              |
-| Gemma 3            | 12B        | 8.1GB | `ollama run gemma3:12b`          |
-| Gemma 3            | 27B        | 17GB  | `ollama run gemma3:27b`          |
-| QwQ                | 32B        | 20GB  | `ollama run qwq`                 |
-| DeepSeek-R1        | 7B         | 4.7GB | `ollama run deepseek-r1`         |
-| DeepSeek-R1        | 671B       | 404GB | `ollama run deepseek-r1:671b`    |
-| Llama 4            | 109B       | 67GB  | `ollama run llama4:scout`        |
-| Llama 4            | 400B       | 245GB | `ollama run llama4:maverick`     |
-| Llama 3.3          | 70B        | 43GB  | `ollama run llama3.3`            |
-| Llama 3.2          | 3B         | 2.0GB | `ollama run llama3.2`            |
-| Llama 3.2          | 1B         | 1.3GB | `ollama run llama3.2:1b`         |
-| Llama 3.2 Vision   | 11B        | 7.9GB | `ollama run llama3.2-vision`     |
-| Llama 3.2 Vision   | 90B        | 55GB  | `ollama run llama3.2-vision:90b` |
-| Llama 3.1          | 8B         | 4.7GB | `ollama run llama3.1`            |
-| Llama 3.1          | 405B       | 231GB | `ollama run llama3.1:405b`       |
-| Phi 4              | 14B        | 9.1GB | `ollama run phi4`                |
-| Phi 4 Mini         | 3.8B       | 2.5GB | `ollama run phi4-mini`           |
-| Mistral            | 7B         | 4.1GB | `ollama run mistral`             |
-| Moondream 2        | 1.4B       | 829MB | `ollama run moondream`           |
-| Neural Chat        | 7B         | 4.1GB | `ollama run neural-chat`         |
-| Starling           | 7B         | 4.1GB | `ollama run starling-lm`         |
-| Code Llama         | 7B         | 3.8GB | `ollama run codellama`           |
-| Llama 2 Uncensored | 7B         | 3.8GB | `ollama run llama2-uncensored`   |
-| LLaVA              | 7B         | 4.5GB | `ollama run llava`               |
-| Granite-3.3         | 8B         | 4.9GB | `ollama run granite3.3`          |
+| Model              | Parameters | Size  | Download                       |
+| ------------------ | ---------- | ----- | ------------------------------ |
+| Llama 3.2          | 3B         | 2.0GB | `ollama run llama3.2`          |
+| Llama 3.2          | 1B         | 1.3GB | `ollama run llama3.2:1b`       |
+| Llama 3.1          | 8B         | 4.7GB | `ollama run llama3.1`          |
+| Llama 3.1          | 70B        | 40GB  | `ollama run llama3.1:70b`      |
+| Llama 3.1          | 405B       | 231GB | `ollama run llama3.1:405b`     |
+| Phi 3 Mini         | 3.8B       | 2.3GB | `ollama run phi3`              |
+| Phi 3 Medium       | 14B        | 7.9GB | `ollama run phi3:medium`       |
+| Gemma 2            | 2B         | 1.6GB | `ollama run gemma2:2b`         |
+| Gemma 2            | 9B         | 5.5GB | `ollama run gemma2`            |
+| Gemma 2            | 27B        | 16GB  | `ollama run gemma2:27b`        |
+| Mistral            | 7B         | 4.1GB | `ollama run mistral`           |
+| Moondream 2        | 1.4B       | 829MB | `ollama run moondream`         |
+| Neural Chat        | 7B         | 4.1GB | `ollama run neural-chat`       |
+| Starling           | 7B         | 4.1GB | `ollama run starling-lm`       |
+| Code Llama         | 7B         | 3.8GB | `ollama run codellama`         |
+| Llama 2 Uncensored | 7B         | 3.8GB | `ollama run llama2-uncensored` |
+| LLaVA              | 7B         | 4.5GB | `ollama run llava`             |
+| Solar              | 10.7B      | 6.1GB | `ollama run solar`             |
 
 > [!NOTE]
 > You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
@@ -98,17 +85,17 @@ Ollama supports importing GGUF models in the Modelfile:
 
 2. Create the model in Ollama
 
-   ```shell
+   ```
    ollama create example -f Modelfile
    ```
 
 3. Run the model
 
-   ```shell
+   ```
    ollama run example
    ```
 
-### Import from Safetensors
+### Import from PyTorch or Safetensors
 
 See the [guide](docs/import.md) on importing models for more information.
 
@@ -116,7 +103,7 @@ See the [guide](docs/import.md) on importing models for more information.
 
 Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3.2` model:
 
-```shell
+```
 ollama pull llama3.2
 ```
 
@@ -143,7 +130,7 @@ ollama run mario
 Hello! It's your friend Mario.
 ```
 
-For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation.
+For more examples, see the [examples](examples) directory. For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation.
 
 ## CLI Reference
 
@@ -151,13 +138,13 @@ For more information on working with a Modelfile, see the [Modelfile](docs/model
 
 `ollama create` is used to create a model from a Modelfile.
 
-```shell
+```
 ollama create mymodel -f ./Modelfile
 ```
 
 ### Pull a model
 
-```shell
+```
 ollama pull llama3.2
 ```
 
@@ -165,13 +152,13 @@ ollama pull llama3.2
 
 ### Remove a model
 
-```shell
+```
 ollama rm llama3.2
 ```
 
 ### Copy a model
 
-```shell
+```
 ollama cp llama3.2 my-model
 ```
 
@@ -190,39 +177,37 @@ I'm a basic program that prints the famous "Hello, world!" message to the consol
 
 ```
 ollama run llava "What's in this image? /Users/jmorgan/Desktop/smile.png"
+The image features a yellow smiley face, which is likely the central focus of the picture.
 ```
 
-> **Output**: The image features a yellow smiley face, which is likely the central focus of the picture.
-
 ### Pass the prompt as an argument
 
-```shell
-ollama run llama3.2 "Summarize this file: $(cat README.md)"
 ```
-
-> **Output**: Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
+$ ollama run llama3.2 "Summarize this file: $(cat README.md)"
+ Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
+```
 
 ### Show model information
 
-```shell
+```
 ollama show llama3.2
 ```
 
 ### List models on your computer
 
-```shell
+```
 ollama list
 ```
 
 ### List which models are currently loaded
 
-```shell
+```
 ollama ps
 ```
 
 ### Stop a model which is currently running
 
-```shell
+```
 ollama stop llama3.2
 ```
 
@@ -238,13 +223,13 @@ See the [developer guide](https://github.com/ollama/ollama/blob/main/docs/develo
 
 Next, start the server:
 
-```shell
+```
 ./ollama serve
 ```
 
 Finally, in a separate shell, run a model:
 
-```shell
+```
 ./ollama run llama3.2
 ```
 
@@ -254,7 +239,7 @@ Ollama has a REST API for running and managing models.
 
 ### Generate a response
 
-```shell
+```
 curl http://localhost:11434/api/generate -d '{
   "model": "llama3.2",
   "prompt":"Why is the sky blue?"
@@ -263,7 +248,7 @@ curl http://localhost:11434/api/generate -d '{
 
 ### Chat with a model
 
-```shell
+```
 curl http://localhost:11434/api/chat -d '{
   "model": "llama3.2",
   "messages": [
@@ -279,7 +264,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
 ### Web & Desktop
 
 - [Open WebUI](https://github.com/open-webui/open-webui)
-- [SwiftChat (macOS with ReactNative)](https://github.com/aws-samples/swift-chat)
 - [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
 - [Hollama](https://github.com/fmaclen/hollama)
 - [Lollms-Webui](https://github.com/ParisNeo/lollms-webui)
@@ -287,13 +271,12 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
 - [HTML UI](https://github.com/rtcfirefly/ollama-ui)
 - [Saddle](https://github.com/jikkuatwork/saddle)
-- [TagSpaces](https://www.tagspaces.org) (A platform for file-based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions)
 - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
 - [Chatbot UI v2](https://github.com/mckaywrigley/chatbot-ui)
 - [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
 - [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui)
 - [Ollamac](https://github.com/kevinhermawan/Ollamac)
-- [big-AGI](https://github.com/enricoros/big-AGI)
+- [big-AGI](https://github.com/enricoros/big-AGI/blob/main/docs/config-local-ollama.md)
 - [Cheshire Cat assistant framework](https://github.com/cheshire-cat-ai/core)
 - [Amica](https://github.com/semperai/amica)
 - [chatd](https://github.com/BruceMacD/chatd)
@@ -313,10 +296,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [AnythingLLM (Docker + MacOs/Windows/Linux native app)](https://github.com/Mintplex-Labs/anything-llm)
 - [Ollama Basic Chat: Uses HyperDiv Reactive UI](https://github.com/rapidarchitect/ollama_basic_chat)
 - [Ollama-chats RPG](https://github.com/drazdra/ollama-chats)
-- [IntelliBar](https://intellibar.app/) (AI-powered assistant for macOS)
-- [Jirapt](https://github.com/AliAhmedNada/jirapt) (Jira Integration to generate issues, tasks, epics)
-- [ojira](https://github.com/AliAhmedNada/ojira) (Jira chrome plugin to easily generate descriptions for tasks)
-- [QA-Pilot](https://github.com/reid41/QA-Pilot) (Interactive chat tool that can leverage Ollama models for rapid understanding and navigation of GitHub code repositories)
+- [QA-Pilot](https://github.com/reid41/QA-Pilot) (Chat with Code Repository)
 - [ChatOllama](https://github.com/sugarforever/chat-ollama) (Open Source Chatbot based on Ollama with Knowledge Bases)
 - [CRAG Ollama Chat](https://github.com/Nagi-ovo/CRAG-Ollama-Chat) (Simple Web Search with Corrective RAG)
 - [RAGFlow](https://github.com/infiniflow/ragflow) (Open-source Retrieval-Augmented Generation engine based on deep document understanding)
@@ -326,18 +306,11 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Ollama RAG Chatbot](https://github.com/datvodinh/rag-chatbot.git) (Local Chat with multiple PDFs using Ollama and RAG)
 - [BrainSoup](https://www.nurgo-software.com/products/brainsoup) (Flexible native client with RAG & multi-agent automation)
 - [macai](https://github.com/Renset/macai) (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
-- [RWKV-Runner](https://github.com/josStorer/RWKV-Runner) (RWKV offline LLM deployment tool, also usable as a client for ChatGPT and Ollama)
-- [Ollama Grid Search](https://github.com/dezoito/ollama-grid-search) (app to evaluate and compare models)
 - [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
-- [Casibase](https://casibase.org) (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support, and multiple large language models.)
 - [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
 - [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
-- [Shinkai Desktop](https://github.com/dcSpark/shinkai-apps) (Two click install Local AI using Ollama + Files + RAG)
-- [AiLama](https://github.com/zeyoyt/ailama) (A Discord User App that allows you to interact with Ollama anywhere in Discord)
+- [AiLama](https://github.com/zeyoyt/ailama) (A Discord User App that allows you to interact with Ollama anywhere in discord )
 - [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
-- [R2R](https://github.com/SciPhi-AI/R2R) (Open-source RAG engine)
-- [Ollama-Kis](https://github.com/elearningshow/ollama-kis) (A simple easy-to-use GUI with sample custom LLM for Drivers Education)
-- [OpenGPA](https://opengpa.org) (Open-source offline-first Enterprise Agentic Application)
 - [Painting Droid](https://github.com/mateuszmigas/painting-droid) (Painting app with AI integrations)
 - [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS)
 - [AI Studio](https://github.com/MindWorkAI/AI-Studio)
@@ -345,89 +318,25 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [LLMStack](https://github.com/trypromptly/LLMStack) (No-code multi-agent framework to build LLM agents and workflows)
 - [BoltAI for Mac](https://boltai.com) (AI Chat Client for Mac)
 - [Harbor](https://github.com/av/harbor) (Containerized LLM Toolkit with Ollama as default backend)
-- [PyGPT](https://github.com/szczyglis-dev/py-gpt) (AI desktop assistant for Linux, Windows, and Mac)
-- [Alpaca](https://github.com/Jeffser/Alpaca) (An Ollama client application for Linux and macOS made with GTK4 and Adwaita)
-- [AutoGPT](https://github.com/Significant-Gravitas/AutoGPT/blob/master/docs/content/platform/ollama.md) (AutoGPT Ollama integration)
 - [Go-CREW](https://www.jonathanhecl.com/go-crew/) (Powerful Offline RAG in Golang)
 - [PartCAD](https://github.com/openvmp/partcad/) (CAD model generation with OpenSCAD and CadQuery)
-- [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot, and Ollama4j
+- [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot and Ollama4j
 - [PyOllaMx](https://github.com/kspviswa/pyOllaMx) - macOS application capable of chatting with both Ollama and Apple MLX models.
-- [Cline](https://github.com/cline/cline) - Formerly known as Claude Dev is a VSCode extension for multi-file/whole-repo coding
+- [Claude Dev](https://github.com/saoudrizwan/claude-dev) - VSCode extension for multi-file/whole-repo coding
 - [Cherry Studio](https://github.com/kangfenmao/cherry-studio) (Desktop client with Ollama support)
-- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
+- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy focused LLM chat interface with optional encryption)
 - [Archyve](https://github.com/nickthecook/archyve) (RAG-enabling document library)
 - [crewAI with Mesop](https://github.com/rapidarchitect/ollama-crew-mesop) (Mesop Web Interface to run crewAI with Ollama)
-- [Tkinter-based client](https://github.com/chyok/ollama-gui) (Python tkinter-based Client for Ollama)
 - [LLMChat](https://github.com/trendy-design/llmchat) (Privacy focused, 100% local, intuitive all-in-one chat interface)
-- [Local Multimodal AI Chat](https://github.com/Leon-Sander/Local-Multimodal-AI-Chat) (Ollama-based LLM Chat with support for multiple features, including PDF RAG, voice chat, image-based interactions, and integration with OpenAI.)
-- [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG and deep research on Mac/Windows/Linux)
-- [OrionChat](https://github.com/EliasPereirah/OrionChat) - OrionChat is a web interface for chatting with different AI providers
+- [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG on Mac/Windows/Linux)
 - [G1](https://github.com/bklieger-groq/g1) (Prototype of using prompting strategies to improve the LLM's reasoning through o1-like reasoning chains.)
-- [Web management](https://github.com/lemonit-eric-mao/ollama-web-management) (Web management page)
-- [Promptery](https://github.com/promptery/promptery) (desktop client for Ollama.)
 - [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
-- [chat-ollama](https://github.com/annilq/chat-ollama) (a React Native client for Ollama)
-- [SpaceLlama](https://github.com/tcsenpai/spacellama) (Firefox and Chrome extension to quickly summarize web pages with ollama in a sidebar)
-- [YouLama](https://github.com/tcsenpai/youlama) (Webapp to quickly summarize any YouTube video, supporting Invidious as well)
-- [DualMind](https://github.com/tcsenpai/dualmind) (Experimental app allowing two models to talk to each other in the terminal or in a web interface)
-- [ollamarama-matrix](https://github.com/h1ddenpr0cess20/ollamarama-matrix) (Ollama chatbot for the Matrix chat protocol)
-- [ollama-chat-app](https://github.com/anan1213095357/ollama-chat-app) (Flutter-based chat app)
-- [Perfect Memory AI](https://www.perfectmemory.ai/) (Productivity AI assists personalized by what you have seen on your screen, heard, and said in the meetings)
-- [Hexabot](https://github.com/hexastack/hexabot) (A conversational AI builder)
-- [Reddit Rate](https://github.com/rapidarchitect/reddit_analyzer) (Search and Rate Reddit topics with a weighted summation)
-- [OpenTalkGpt](https://github.com/adarshM84/OpenTalkGpt) (Chrome Extension to manage open-source models supported by Ollama, create custom models, and chat with models from a user-friendly UI)
-- [VT](https://github.com/vinhnx/vt.ai) (A minimal multimodal AI chat app, with dynamic conversation routing. Supports local models via Ollama)
-- [Nosia](https://github.com/nosia-ai/nosia) (Easy to install and use RAG platform based on Ollama)
-- [Witsy](https://github.com/nbonamy/witsy) (An AI Desktop application available for Mac/Windows/Linux)
-- [Abbey](https://github.com/US-Artificial-Intelligence/abbey) (A configurable AI interface server with notebooks, document storage, and YouTube support)
-- [Minima](https://github.com/dmayboroda/minima) (RAG with on-premises or fully local workflow)
-- [aidful-ollama-model-delete](https://github.com/AidfulAI/aidful-ollama-model-delete) (User interface for simplified model cleanup)
-- [Perplexica](https://github.com/ItzCrazyKns/Perplexica) (An AI-powered search engine & an open-source alternative to Perplexity AI)
-- [Ollama Chat WebUI for Docker ](https://github.com/oslook/ollama-webui) (Support for local docker deployment, lightweight ollama webui)
-- [AI Toolkit for Visual Studio Code](https://aka.ms/ai-tooklit/ollama-docs) (Microsoft-official VSCode extension to chat, test, evaluate models with Ollama support, and use them in your AI applications.)
-- [MinimalNextOllamaChat](https://github.com/anilkay/MinimalNextOllamaChat) (Minimal Web UI for Chat and Model Control)
-- [Chipper](https://github.com/TilmanGriesel/chipper) AI interface for tinkerers (Ollama, Haystack RAG, Python)
-- [ChibiChat](https://github.com/CosmicEventHorizon/ChibiChat) (Kotlin-based Android app to chat with Ollama and Koboldcpp API endpoints)
-- [LocalLLM](https://github.com/qusaismael/localllm) (Minimal Web-App to run ollama models on it with a GUI)
-- [Ollamazing](https://github.com/buiducnhat/ollamazing) (Web extension to run Ollama models)
-- [OpenDeepResearcher-via-searxng](https://github.com/benhaotang/OpenDeepResearcher-via-searxng) (A Deep Research equivalent endpoint with Ollama support for running locally)
-- [AntSK](https://github.com/AIDotNet/AntSK) (Out-of-the-box & Adaptable RAG Chatbot)
-- [MaxKB](https://github.com/1Panel-dev/MaxKB/) (Ready-to-use & flexible RAG Chatbot)
-- [yla](https://github.com/danielekp/yla) (Web interface to freely interact with your customized models)
-- [LangBot](https://github.com/RockChinQ/LangBot) (LLM-based instant messaging bots platform, with Agents, RAG features, supports multiple platforms)
-- [1Panel](https://github.com/1Panel-dev/1Panel/) (Web-based Linux Server Management Tool)
-- [AstrBot](https://github.com/Soulter/AstrBot/) (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration)
-- [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
-- [Flufy](https://github.com/Aharon-Bensadoun/Flufy) (A beautiful chat interface for interacting with Ollama's API. Built with React, TypeScript, and Material-UI.)
-- [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
-- [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history
-- [Ollamb](https://github.com/hengkysteen/ollamb) (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the [web demo](https://hengkysteen.github.io/demo/ollamb/).)
-- [Writeopia](https://github.com/Writeopia/Writeopia) (Text editor with integration with Ollama)
-- [AppFlowy](https://github.com/AppFlowy-IO/AppFlowy) (AI collaborative workspace with Ollama, cross-platform and self-hostable)
-- [Lumina](https://github.com/cushydigit/lumina.git) (A lightweight, minimal React.js frontend for interacting with Ollama servers)
-- [Tiny Notepad](https://pypi.org/project/tiny-notepad) (A lightweight, notepad-like interface to chat with ollama available on PyPI)
-- [macLlama (macOS native)](https://github.com/hellotunamayo/macLlama) (A native macOS GUI application for interacting with Ollama models, featuring a chat interface.) 
-- [GPTranslate](https://github.com/philberndt/GPTranslate) (A fast and lightweight, AI powered desktop translation application written with Rust and Tauri. Features real-time translation with OpenAI/Azure/Ollama.)
-- [ollama launcher](https://github.com/NGC13009/ollama-launcher) (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.)
-- [ai-hub](https://github.com/Aj-Seven/ai-hub) (AI Hub supports multiple models via API keys and Chat support via Ollama API.)
-- [Mayan EDMS](https://gitlab.com/mayan-edms/mayan-edms) (Open source document management system to organize, tag, search, and automate your files with powerful Ollama driven workflows.)
-- [Serene Pub](https://github.com/doolijb/serene-pub) (Beginner friendly, open source AI Roleplaying App for Windows, Mac OS and Linux. Search, download and use models with Ollama all inside the app.)
-- [Andes](https://github.com/aqerd/andes) (A Visual Studio Code extension that provides a local UI interface for Ollama models)
-- [Clueless](https://github.com/KashyapTan/clueless) (Open Source & Local Cluely: A desktop application LLM assistant to help you talk to anything on your screen using locally served Ollama models. Also undetectable to screenshare)
-- [ollama-co2](https://github.com/carbonatedWaterOrg/ollama-co2) (FastAPI web interface for monitoring and managing local and remote Ollama servers with real-time model monitoring and concurrent downloads)
-
-### Cloud
-
-- [Google Cloud](https://cloud.google.com/run/docs/tutorials/gpu-gemma2-with-ollama)
-- [Fly.io](https://fly.io/docs/python/do-more/add-ollama/)
-- [Koyeb](https://www.koyeb.com/deploy/ollama)
 
 ### Terminal
 
 - [oterm](https://github.com/ggozad/oterm)
 - [Ellama Emacs client](https://github.com/s-kostyaev/ellama)
 - [Emacs client](https://github.com/zweifisch/ollama)
-- [neollama](https://github.com/paradoxical-dev/neollama) UI client for interacting with models from within Neovim
 - [gen.nvim](https://github.com/David-Kunz/gen.nvim)
 - [ollama.nvim](https://github.com/nomnivore/ollama.nvim)
 - [ollero.nvim](https://github.com/marco-souza/ollero.nvim)
@@ -437,7 +346,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Oatmeal](https://github.com/dustinblackman/oatmeal)
 - [cmdh](https://github.com/pgibler/cmdh)
 - [ooo](https://github.com/npahlfer/ooo)
-- [shell-pilot](https://github.com/reid41/shell-pilot)(Interact with models via pure shell scripts on Linux or macOS)
+- [shell-pilot](https://github.com/reid41/shell-pilot)
 - [tenere](https://github.com/pythops/tenere)
 - [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/).
 - [typechat-cli](https://github.com/anaisbetts/typechat-cli)
@@ -445,58 +354,35 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [tlm](https://github.com/yusufcanb/tlm)
 - [podman-ollama](https://github.com/ericcurtin/podman-ollama)
 - [gollama](https://github.com/sammcj/gollama)
-- [ParLlama](https://github.com/paulrobello/parllama)
 - [Ollama eBook Summary](https://github.com/cognitivetech/ollama-ebook-summary/)
 - [Ollama Mixture of Experts (MOE) in 50 lines of code](https://github.com/rapidarchitect/ollama_moe)
 - [vim-intelligence-bridge](https://github.com/pepo-ec/vim-intelligence-bridge) Simple interaction of "Ollama" with the Vim editor
-- [x-cmd ollama](https://x-cmd.com/mod/ollama)
-- [bb7](https://github.com/drunkwcodes/bb7)
-- [SwollamaCLI](https://github.com/marcusziade/Swollama) bundled with the Swollama Swift package. [Demo](https://github.com/marcusziade/Swollama?tab=readme-ov-file#cli-usage)
-- [aichat](https://github.com/sigoden/aichat) All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
-- [PowershAI](https://github.com/rrg92/powershai) PowerShell module that brings AI to terminal on Windows, including support for Ollama
-- [DeepShell](https://github.com/Abyss-c0re/deepshell) Your self-hosted AI assistant. Interactive Shell, Files and Folders analysis.
-- [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama.
-- [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull, and download models from Ollama Registry in your terminal.
-- [GGUF-to-Ollama](https://github.com/jonathanhecl/gguf-to-ollama) - Importing GGUF to Ollama made easy (multiplatform)
-- [AWS-Strands-With-Ollama](https://github.com/rapidarchitect/ollama_strands) - AWS Strands Agents with Ollama Examples
-- [ollama-multirun](https://github.com/attogram/ollama-multirun) - A bash shell script to run a single prompt against any or all of your locally installed ollama models, saving the output and performance statistics as easily navigable web pages. ([Demo](https://attogram.github.io/ai_test_zone/))
-- [ollama-bash-toolshed](https://github.com/attogram/ollama-bash-toolshed) - Bash scripts to chat with tool using models. Add new tools to your shed with ease. Runs on Ollama.
 
 ### Apple Vision Pro
-
-- [SwiftChat](https://github.com/aws-samples/swift-chat) (Cross-platform AI chat app supporting Apple Vision Pro via "Designed for iPad")
 - [Enchanted](https://github.com/AugustDev/enchanted)
 
 ### Database
 
-- [pgai](https://github.com/timescale/pgai) - PostgreSQL as a vector database (Create and search embeddings from Ollama models using pgvector)
-   - [Get started guide](https://github.com/timescale/pgai/blob/main/docs/vectorizer-quick-start.md)
 - [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) (Connects Ollama models with nearly 200 data platforms and apps)
 - [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) with [example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama)
-- [Kangaroo](https://github.com/dbkangaroo/kangaroo) (AI-powered SQL client and admin tool for popular databases)
 
 ### Package managers
 
 - [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/)
 - [Gentoo](https://github.com/gentoo/guru/tree/master/app-misc/ollama)
-- [Homebrew](https://formulae.brew.sh/formula/ollama)
 - [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama)
 - [Guix channel](https://codeberg.org/tusharhero/ollama-guix)
-- [Nix package](https://search.nixos.org/packages?show=ollama&from=0&size=50&sort=relevance&type=packages&query=ollama)
+- [Nix package](https://search.nixos.org/packages?channel=24.05&show=ollama&from=0&size=50&sort=relevance&type=packages&query=ollama)
 - [Flox](https://flox.dev/blog/ollama-part-one)
 
 ### Libraries
 
-- [LangChain](https://python.langchain.com/docs/integrations/chat/ollama/) and [LangChain.js](https://js.langchain.com/docs/integrations/chat/ollama/) with [example](https://js.langchain.com/docs/tutorials/local_rag/)
+- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/integrations/chat/ollama/) with [example](https://js.langchain.com/docs/tutorials/local_rag/)
 - [Firebase Genkit](https://firebase.google.com/docs/genkit/plugins/ollama)
 - [crewAI](https://github.com/crewAIInc/crewAI)
-- [Yacana](https://remembersoftwares.github.io/yacana/) (User-friendly multi-agent framework for brainstorming and executing predetermined flows with built-in tool integration)
-- [Spring AI](https://github.com/spring-projects/spring-ai) with [reference](https://docs.spring.io/spring-ai/reference/api/chat/ollama-chat.html) and [example](https://github.com/tzolov/ollama-tools)
 - [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
 - [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
 - [LangChainRust](https://github.com/Abraxas-365/langchain-rust) with [example](https://github.com/Abraxas-365/langchain-rust/blob/main/examples/llm_ollama.rs)
-- [LangChain for .NET](https://github.com/tryAGI/LangChain) with [example](https://github.com/tryAGI/LangChain/blob/main/examples/LangChain.Samples.OpenAI/Program.cs)
-- [LLPhant](https://github.com/theodo-group/LLPhant?tab=readme-ov-file#ollama)
 - [LlamaIndex](https://docs.llamaindex.ai/en/stable/examples/llm/ollama/) and [LlamaIndexTS](https://ts.llamaindex.ai/modules/llms/available_llms/ollama)
 - [LiteLLM](https://github.com/BerriAI/litellm)
 - [OllamaFarm for Go](https://github.com/presbrey/ollamafarm)
@@ -521,46 +407,25 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Portkey](https://portkey.ai/docs/welcome/integration-guides/ollama)
 - [PromptingTools.jl](https://github.com/svilupp/PromptingTools.jl) with an [example](https://svilupp.github.io/PromptingTools.jl/dev/examples/working_with_ollama)
 - [LlamaScript](https://github.com/Project-Llama/llamascript)
-- [llm-axe](https://github.com/emirsahin1/llm-axe) (Python Toolkit for Building LLM Powered Apps)
 - [Gollm](https://docs.gollm.co/examples/ollama-example)
-- [Gollama for Golang](https://github.com/jonathanhecl/gollama)
 - [Ollamaclient for Golang](https://github.com/xyproto/ollamaclient)
 - [High-level function abstraction in Go](https://gitlab.com/tozd/go/fun)
 - [Ollama PHP](https://github.com/ArdaGnsrn/ollama-php)
 - [Agents-Flex for Java](https://github.com/agents-flex/agents-flex) with [example](https://github.com/agents-flex/agents-flex/tree/main/agents-flex-llm/agents-flex-llm-ollama/src/test/java/com/agentsflex/llm/ollama)
-- [Parakeet](https://github.com/parakeet-nest/parakeet) is a GoLang library, made to simplify the development of small generative AI applications with Ollama.
-- [Haverscript](https://github.com/andygill/haverscript) with [examples](https://github.com/andygill/haverscript/tree/main/examples)
 - [Ollama for Swift](https://github.com/mattt/ollama-swift)
-- [Swollama for Swift](https://github.com/marcusziade/Swollama) with [DocC](https://marcusziade.github.io/Swollama/documentation/swollama/)
-- [GoLamify](https://github.com/prasad89/golamify)
-- [Ollama for Haskell](https://github.com/tusharad/ollama-haskell)
-- [multi-llm-ts](https://github.com/nbonamy/multi-llm-ts) (A Typescript/JavaScript library allowing access to different LLM in a unified API)
-- [LlmTornado](https://github.com/lofcz/llmtornado) (C# library providing a unified interface for major FOSS & Commercial inference APIs)
-- [Ollama for Zig](https://github.com/dravenk/ollama-zig)
-- [Abso](https://github.com/lunary-ai/abso) (OpenAI-compatible TypeScript SDK for any LLM provider)
-- [Nichey](https://github.com/goodreasonai/nichey) is a Python package for generating custom wikis for your research topic
-- [Ollama for D](https://github.com/kassane/ollama-d)
-- [OllamaPlusPlus](https://github.com/HardCodeDev777/OllamaPlusPlus) (Very simple C++ library for Ollama)
-- [any-llm](https://github.com/mozilla-ai/any-llm) (A single interface to use different llm providers by [mozilla.ai](https://www.mozilla.ai/))
-- [any-agent](https://github.com/mozilla-ai/any-agent) (A single interface to use and evaluate different agent frameworks by [mozilla.ai](https://www.mozilla.ai/))
-- [Neuro SAN](https://github.com/cognizant-ai-lab/neuro-san-studio) (Data-driven multi-agent orchestration framework) with [example](https://github.com/cognizant-ai-lab/neuro-san-studio/blob/main/docs/user_guide.md#ollama)
 
 ### Mobile
 
-- [SwiftChat](https://github.com/aws-samples/swift-chat) (Lightning-fast Cross-platform AI chat app with native UI for Android, iOS, and iPad)
 - [Enchanted](https://github.com/AugustDev/enchanted)
 - [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
 - [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
-- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
-- [Ollama Android Chat](https://github.com/sunshine0523/OllamaServer) (No need for Termux, start the Ollama service with one click on an Android device)
-- [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
+- [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy focused LLM chat interface with optional encryption)
 
 ### Extensions & Plugins
 
 - [Raycast extension](https://github.com/MassimilianoPasquini97/raycast_ollama)
 - [Discollama](https://github.com/mxyng/discollama) (Discord bot inside the Ollama discord channel)
 - [Continue](https://github.com/continuedev/continue)
-- [Vibe](https://github.com/thewh1teagle/vibe) (Transcribe and analyze meetings with Ollama)
 - [Obsidian Ollama plugin](https://github.com/hinterdupfinger/obsidian-ollama)
 - [Logseq Ollama plugin](https://github.com/omagdy7/ollama-logseq)
 - [NotesOllama](https://github.com/andersrex/notesollama) (Apple Notes Ollama plugin)
@@ -575,7 +440,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
 - [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
 - [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
-- [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use Ollama as a copilot like GitHub Copilot)
+- [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use ollama as a copilot like Github copilot)
 - [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
 - [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and Hugging Face)
 - [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
@@ -583,37 +448,14 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [AI Telegram Bot](https://github.com/tusharhero/aitelegrambot) (Telegram bot using Ollama in backend)
 - [AI ST Completion](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (Sublime Text 4 AI assistant plugin with Ollama support)
 - [Discord-Ollama Chat Bot](https://github.com/kevinthedang/discord-ollama) (Generalized TypeScript Discord Bot w/ Tuning Documentation)
-- [ChatGPTBox: All in one browser extension](https://github.com/josStorer/chatGPTBox) with [Integrating Tutorial](https://github.com/josStorer/chatGPTBox/issues/616#issuecomment-1975186467)
 - [Discord AI chat/moderation bot](https://github.com/rapmd73/Companion) Chat/moderation bot written in python. Uses Ollama to create personalities.
-- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depend on ollama server)
-- [Terraform AWS Ollama & Open WebUI](https://github.com/xuyangbocn/terraform-aws-self-host-llm) (A Terraform module to deploy on AWS a ready-to-use Ollama service, together with its front-end Open WebUI service.)
-- [node-red-contrib-ollama](https://github.com/jakubburkiewicz/node-red-contrib-ollama)
-- [Local AI Helper](https://github.com/ivostoykov/localAI) (Chrome and Firefox extensions that enable interactions with the active tab and customisable API endpoints. Includes secure storage for user prompts.)
-- [vnc-lm](https://github.com/jake83741/vnc-lm) (Discord bot for messaging with LLMs through Ollama and LiteLLM. Seamlessly move between local and flagship models.)
+- [Headless Ollama](https://github.com/nischalj10/headless-ollama) (Scripts to automatically install ollama client & models on any OS for apps that depends on ollama server)
+- [vnc-lm](https://github.com/jk011ru/vnc-lm) (A containerized Discord bot with support for attachments and web links)
 - [LSP-AI](https://github.com/SilasMarvin/lsp-ai) (Open-source language server for AI-powered functionality)
 - [QodeAssist](https://github.com/Palm1r/QodeAssist) (AI-powered coding assistant plugin for Qt Creator)
 - [Obsidian Quiz Generator plugin](https://github.com/ECuiDev/obsidian-quiz-generator)
-- [AI Summmary Helper plugin](https://github.com/philffm/ai-summary-helper)
-- [TextCraft](https://github.com/suncloudsmoon/TextCraft) (Copilot in Word alternative using Ollama)
-- [Alfred Ollama](https://github.com/zeitlings/alfred-ollama) (Alfred Workflow)
-- [TextLLaMA](https://github.com/adarshM84/TextLLaMA) A Chrome Extension that helps you write emails, correct grammar, and translate into any language
-- [Simple-Discord-AI](https://github.com/zyphixor/simple-discord-ai)
-- [LLM Telegram Bot](https://github.com/innightwolfsleep/llm_telegram_bot) (telegram bot, primary for RP. Oobabooga-like buttons, [A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui) API integration e.t.c)
-- [mcp-llm](https://github.com/sammcj/mcp-llm) (MCP Server to allow LLMs to call other LLMs)
-- [SimpleOllamaUnity](https://github.com/HardCodeDev777/SimpleOllamaUnity) (Unity Engine extension for communicating with Ollama in a few lines of code. Also works at runtime)
-- [UnityCodeLama](https://github.com/HardCodeDev777/UnityCodeLama) (Unity Edtior tool to analyze scripts via Ollama)
-- [NativeMind](https://github.com/NativeMindBrowser/NativeMindExtension) (Private, on-device AI Assistant, no cloud dependencies)
-- [GMAI - Gradle Managed AI](https://gmai.premex.se/) (Gradle plugin for automated Ollama lifecycle management during build phases)
-- [NOMYO Router](https://github.com/nomyo-ai/nomyo-router) (A transparent Ollama proxy with model deployment aware routing which auto-manages multiple Ollama instances in a given network)
 
 ### Supported backends
 
-- [llama.cpp](https://github.com/ggml-org/llama.cpp) project founded by Georgi Gerganov.
+- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.
 
-### Observability
-- [Opik](https://www.comet.com/docs/opik/cookbook/ollama) is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native intergration to Ollama.
-- [Lunary](https://lunary.ai/docs/integrations/ollama) is the leading open-source LLM observability platform. It provides a variety of enterprise-grade features such as real-time analytics, prompt templates management, PII masking, and comprehensive agent tracing.
-- [OpenLIT](https://github.com/openlit/openlit) is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics.
-- [HoneyHive](https://docs.honeyhive.ai/integrations/ollama) is an AI observability and evaluation platform for AI agents. Use HoneyHive to evaluate agent performance, interrogate failures, and monitor quality in production.
-- [Langfuse](https://langfuse.com/docs/integrations/ollama) is an open source LLM observability platform that enables teams to collaboratively monitor, evaluate and debug AI applications.
-- [MLflow Tracing](https://mlflow.org/docs/latest/llms/tracing/index.html#automatic-tracing) is an open source LLM observability tool with a convenient API to log and visualize traces, making it easy to debug and evaluate GenAI applications.

api/client.go

@@ -10,7 +10,7 @@
 // repository].
 //
 // [the API documentation]: https://github.com/ollama/ollama/blob/main/docs/api.md
-// [in the GitHub repository]: https://github.com/ollama/ollama/tree/main/api/examples
+// [in the GitHub repository]: https://github.com/ollama/ollama/tree/main/examples
 package api
 
 import (
@@ -24,10 +24,7 @@ import (
 	"net/http"
 	"net/url"
 	"runtime"
-	"strconv"
-	"time"
 
-	"github.com/ollama/ollama/auth"
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/version"
@@ -58,7 +55,7 @@ func checkError(resp *http.Response, body []byte) error {
 
 // ClientFromEnvironment creates a new [Client] using configuration from the
 // environment variable OLLAMA_HOST, which points to the network host and
-// port on which the ollama service is listening. The format of this variable
+// port on which the ollama service is listenting. The format of this variable
 // is:
 //
 //	<scheme>://<host>:<port>
@@ -79,14 +76,6 @@ func NewClient(base *url.URL, http *http.Client) *Client {
 	}
 }
 
-func getAuthorizationToken(ctx context.Context, challenge string) (string, error) {
-	token, err := auth.Sign(ctx, []byte(challenge))
-	if err != nil {
-		return "", err
-	}
-	return token, nil
-}
-
 func (c *Client) do(ctx context.Context, method, path string, reqData, respData any) error {
 	var reqBody io.Reader
 	var data []byte
@@ -108,21 +97,6 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 	}
 
 	requestURL := c.base.JoinPath(path)
-
-	var token string
-	if envconfig.UseAuth() || c.base.Hostname() == "ollama.com" {
-		now := strconv.FormatInt(time.Now().Unix(), 10)
-		chal := fmt.Sprintf("%s,%s?ts=%s", method, path, now)
-		token, err = getAuthorizationToken(ctx, chal)
-		if err != nil {
-			return err
-		}
-
-		q := requestURL.Query()
-		q.Set("ts", now)
-		requestURL.RawQuery = q.Encode()
-	}
-
 	request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), reqBody)
 	if err != nil {
 		return err
@@ -132,10 +106,6 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 	request.Header.Set("Accept", "application/json")
 	request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
 
-	if token != "" {
-		request.Header.Set("Authorization", token)
-	}
-
 	respObj, err := c.http.Do(request)
 	if err != nil {
 		return err
@@ -162,7 +132,7 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
 const maxBufferSize = 512 * format.KiloByte
 
 func (c *Client) stream(ctx context.Context, method, path string, data any, fn func([]byte) error) error {
-	var buf io.Reader
+	var buf *bytes.Buffer
 	if data != nil {
 		bts, err := json.Marshal(data)
 		if err != nil {
@@ -173,22 +143,6 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 	}
 
 	requestURL := c.base.JoinPath(path)
-
-	var token string
-	if envconfig.UseAuth() || c.base.Hostname() == "ollama.com" {
-		var err error
-		now := strconv.FormatInt(time.Now().Unix(), 10)
-		chal := fmt.Sprintf("%s,%s?ts=%s", method, path, now)
-		token, err = getAuthorizationToken(ctx, chal)
-		if err != nil {
-			return err
-		}
-
-		q := requestURL.Query()
-		q.Set("ts", now)
-		requestURL.RawQuery = q.Encode()
-	}
-
 	request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), buf)
 	if err != nil {
 		return err
@@ -198,10 +152,6 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 	request.Header.Set("Accept", "application/x-ndjson")
 	request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
 
-	if token != "" {
-		request.Header.Set("Authorization", token)
-	}
-
 	response, err := c.http.Do(request)
 	if err != nil {
 		return err
@@ -222,6 +172,10 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 			return fmt.Errorf("unmarshal: %w", err)
 		}
 
+		if errorResponse.Error != "" {
+			return errors.New(errorResponse.Error)
+		}
+
 		if response.StatusCode >= http.StatusBadRequest {
 			return StatusError{
 				StatusCode:   response.StatusCode,
@@ -230,10 +184,6 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 			}
 		}
 
-		if errorResponse.Error != "" {
-			return errors.New(errorResponse.Error)
-		}
-
 		if err := fn(bts); err != nil {
 			return err
 		}

api/client_test.go

@@ -1,12 +1,6 @@
 package api
 
 import (
-	"encoding/json"
-	"fmt"
-	"net/http"
-	"net/http/httptest"
-	"net/url"
-	"strings"
 	"testing"
 )
 
@@ -49,216 +43,3 @@ func TestClientFromEnvironment(t *testing.T) {
 		})
 	}
 }
-
-// testError represents an internal error type with status code and message
-// this is used since the error response from the server is not a standard error struct
-type testError struct {
-	message    string
-	statusCode int
-}
-
-func (e testError) Error() string {
-	return e.message
-}
-
-func TestClientStream(t *testing.T) {
-	testCases := []struct {
-		name      string
-		responses []any
-		wantErr   string
-	}{
-		{
-			name: "immediate error response",
-			responses: []any{
-				testError{
-					message:    "test error message",
-					statusCode: http.StatusBadRequest,
-				},
-			},
-			wantErr: "test error message",
-		},
-		{
-			name: "error after successful chunks, ok response",
-			responses: []any{
-				ChatResponse{Message: Message{Content: "partial response 1"}},
-				ChatResponse{Message: Message{Content: "partial response 2"}},
-				testError{
-					message:    "mid-stream error",
-					statusCode: http.StatusOK,
-				},
-			},
-			wantErr: "mid-stream error",
-		},
-		{
-			name: "http status error takes precedence over general error",
-			responses: []any{
-				testError{
-					message:    "custom error message",
-					statusCode: http.StatusInternalServerError,
-				},
-			},
-			wantErr: "500",
-		},
-		{
-			name: "successful stream completion",
-			responses: []any{
-				ChatResponse{Message: Message{Content: "chunk 1"}},
-				ChatResponse{Message: Message{Content: "chunk 2"}},
-				ChatResponse{
-					Message:    Message{Content: "final chunk"},
-					Done:       true,
-					DoneReason: "stop",
-				},
-			},
-		},
-	}
-
-	for _, tc := range testCases {
-		t.Run(tc.name, func(t *testing.T) {
-			ts := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-				flusher, ok := w.(http.Flusher)
-				if !ok {
-					t.Fatal("expected http.Flusher")
-				}
-
-				w.Header().Set("Content-Type", "application/x-ndjson")
-
-				for _, resp := range tc.responses {
-					if errResp, ok := resp.(testError); ok {
-						w.WriteHeader(errResp.statusCode)
-						err := json.NewEncoder(w).Encode(map[string]string{
-							"error": errResp.message,
-						})
-						if err != nil {
-							t.Fatal("failed to encode error response:", err)
-						}
-						return
-					}
-
-					if err := json.NewEncoder(w).Encode(resp); err != nil {
-						t.Fatalf("failed to encode response: %v", err)
-					}
-					flusher.Flush()
-				}
-			}))
-			defer ts.Close()
-
-			client := NewClient(&url.URL{Scheme: "http", Host: ts.Listener.Addr().String()}, http.DefaultClient)
-
-			var receivedChunks []ChatResponse
-			err := client.stream(t.Context(), http.MethodPost, "/v1/chat", nil, func(chunk []byte) error {
-				var resp ChatResponse
-				if err := json.Unmarshal(chunk, &resp); err != nil {
-					return fmt.Errorf("failed to unmarshal chunk: %w", err)
-				}
-				receivedChunks = append(receivedChunks, resp)
-				return nil
-			})
-
-			if tc.wantErr != "" {
-				if err == nil {
-					t.Fatal("expected error but got nil")
-				}
-				if !strings.Contains(err.Error(), tc.wantErr) {
-					t.Errorf("expected error containing %q, got %v", tc.wantErr, err)
-				}
-				return
-			}
-			if err != nil {
-				t.Errorf("unexpected error: %v", err)
-			}
-		})
-	}
-}
-
-func TestClientDo(t *testing.T) {
-	testCases := []struct {
-		name     string
-		response any
-		wantErr  string
-	}{
-		{
-			name: "immediate error response",
-			response: testError{
-				message:    "test error message",
-				statusCode: http.StatusBadRequest,
-			},
-			wantErr: "test error message",
-		},
-		{
-			name: "server error response",
-			response: testError{
-				message:    "internal error",
-				statusCode: http.StatusInternalServerError,
-			},
-			wantErr: "internal error",
-		},
-		{
-			name: "successful response",
-			response: struct {
-				ID      string `json:"id"`
-				Success bool   `json:"success"`
-			}{
-				ID:      "msg_123",
-				Success: true,
-			},
-		},
-	}
-
-	for _, tc := range testCases {
-		t.Run(tc.name, func(t *testing.T) {
-			ts := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-				if errResp, ok := tc.response.(testError); ok {
-					w.WriteHeader(errResp.statusCode)
-					err := json.NewEncoder(w).Encode(map[string]string{
-						"error": errResp.message,
-					})
-					if err != nil {
-						t.Fatal("failed to encode error response:", err)
-					}
-					return
-				}
-
-				w.Header().Set("Content-Type", "application/json")
-				if err := json.NewEncoder(w).Encode(tc.response); err != nil {
-					t.Fatalf("failed to encode response: %v", err)
-				}
-			}))
-			defer ts.Close()
-
-			client := NewClient(&url.URL{Scheme: "http", Host: ts.Listener.Addr().String()}, http.DefaultClient)
-
-			var resp struct {
-				ID      string `json:"id"`
-				Success bool   `json:"success"`
-			}
-			err := client.do(t.Context(), http.MethodPost, "/v1/messages", nil, &resp)
-
-			if tc.wantErr != "" {
-				if err == nil {
-					t.Fatalf("got nil, want error %q", tc.wantErr)
-				}
-				if err.Error() != tc.wantErr {
-					t.Errorf("error message mismatch: got %q, want %q", err.Error(), tc.wantErr)
-				}
-				return
-			}
-
-			if err != nil {
-				t.Fatalf("got error %q, want nil", err)
-			}
-
-			if expectedResp, ok := tc.response.(struct {
-				ID      string `json:"id"`
-				Success bool   `json:"success"`
-			}); ok {
-				if resp.ID != expectedResp.ID {
-					t.Errorf("response ID mismatch: got %q, want %q", resp.ID, expectedResp.ID)
-				}
-				if resp.Success != expectedResp.Success {
-					t.Errorf("response Success mismatch: got %v, want %v", resp.Success, expectedResp.Success)
-				}
-			}
-		})
-	}
-}

api/examples/README.md

@@ -1,18 +0,0 @@
-# Ollama API Examples
-
-Run the examples in this directory with:
-
-```shell
-go run example_name/main.go
-```
-
-## Chat - Chat with a model
-- [chat/main.go](chat/main.go)
-
-## Generate - Generate text from a model
-- [generate/main.go](generate/main.go)
-- [generate-streaming/main.go](generate-streaming/main.go)
-
-## Pull - Pull a model
-- [pull-progress/main.go](pull-progress/main.go)
-

api/types.go

@@ -10,12 +10,9 @@ import (
 	"strconv"
 	"strings"
 	"time"
-
-	"github.com/ollama/ollama/envconfig"
-	"github.com/ollama/ollama/types/model"
 )
 
-// StatusError is an error with an HTTP status code and message.
+// StatusError is an error with and HTTP status code.
 type StatusError struct {
 	StatusCode   int
 	Status       string
@@ -60,7 +57,7 @@ type GenerateRequest struct {
 	Template string `json:"template"`
 
 	// Context is the context parameter returned from a previous call to
-	// [Client.Generate]. It can be used to keep a short conversational memory.
+	// Generate call. It can be used to keep a short conversational memory.
 	Context []int `json:"context,omitempty"`
 
 	// Stream specifies whether the response is streaming; it is true by default.
@@ -70,30 +67,19 @@ type GenerateRequest struct {
 	Raw bool `json:"raw,omitempty"`
 
 	// Format specifies the format to return a response in.
-	Format json.RawMessage `json:"format,omitempty"`
+	Format string `json:"format"`
 
 	// KeepAlive controls how long the model will stay loaded in memory following
 	// this request.
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
-	// Images is an optional list of raw image bytes accompanying this
+	// Images is an optional list of base64-encoded images accompanying this
 	// request, for multimodal models.
 	Images []ImageData `json:"images,omitempty"`
 
 	// Options lists model-specific options. For example, temperature can be
 	// set through this field, if the model supports it.
-	Options map[string]any `json:"options"`
-
-	// Think controls whether thinking/reasoning models will think before
-	// responding. Can be a boolean (true/false) or a string ("high", "medium", "low")
-	// for supported models. Needs to be a pointer so we can distinguish between false
-	// (request that thinking _not_ be used) and unset (use the old behavior
-	// before this option was introduced)
-	Think *ThinkValue `json:"think,omitempty"`
-
-	// DebugRenderOnly is a debug option that, when set to true, returns the rendered
-	// template instead of calling the model.
-	DebugRenderOnly bool `json:"_debug_render_only,omitempty"`
+	Options map[string]interface{} `json:"options"`
 }
 
 // ChatRequest describes a request sent by [Client.Chat].
@@ -104,30 +90,21 @@ type ChatRequest struct {
 	// Messages is the messages of the chat - can be used to keep a chat memory.
 	Messages []Message `json:"messages"`
 
-	// Stream enables streaming of returned responses; true by default.
+	// Stream enable streaming of returned response; true by default.
 	Stream *bool `json:"stream,omitempty"`
 
 	// Format is the format to return the response in (e.g. "json").
-	Format json.RawMessage `json:"format,omitempty"`
+	Format string `json:"format"`
 
 	// KeepAlive controls how long the model will stay loaded into memory
-	// following the request.
+	// followin the request.
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
 	// Tools is an optional list of tools the model has access to.
 	Tools `json:"tools,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]any `json:"options"`
-
-	// Think controls whether thinking/reasoning models will think before
-	// responding. Can be a boolean (true/false) or a string ("high", "medium", "low")
-	// for supported models.
-	Think *ThinkValue `json:"think,omitempty"`
-
-	// DebugRenderOnly is a debug option that, when set to true, returns the rendered
-	// template instead of calling the model.
-	DebugRenderOnly bool `json:"_debug_render_only,omitempty"`
+	Options map[string]interface{} `json:"options"`
 }
 
 type Tools []Tool
@@ -146,14 +123,10 @@ func (t Tool) String() string {
 // role ("system", "user", or "assistant"), the content and an optional list
 // of images.
 type Message struct {
-	Role    string `json:"role"`
-	Content string `json:"content"`
-	// Thinking contains the text that was inside thinking tags in the
-	// original model output when ChatRequest.Think is enabled.
-	Thinking  string      `json:"thinking,omitempty"`
+	Role      string      `json:"role"`
+	Content   string      `json:"content"`
 	Images    []ImageData `json:"images,omitempty"`
 	ToolCalls []ToolCall  `json:"tool_calls,omitempty"`
-	ToolName  string      `json:"tool_name,omitempty"`
 }
 
 func (m *Message) UnmarshalJSON(b []byte) error {
@@ -173,7 +146,6 @@ type ToolCall struct {
 }
 
 type ToolCallFunction struct {
-	Index     int                       `json:"index,omitempty"`
 	Name      string                    `json:"name"`
 	Arguments ToolCallFunctionArguments `json:"arguments"`
 }
@@ -187,122 +159,21 @@ func (t *ToolCallFunctionArguments) String() string {
 
 type Tool struct {
 	Type     string       `json:"type"`
-	Items    any          `json:"items,omitempty"`
 	Function ToolFunction `json:"function"`
 }
 
-// PropertyType can be either a string or an array of strings
-type PropertyType []string
-
-// UnmarshalJSON implements the json.Unmarshaler interface
-func (pt *PropertyType) UnmarshalJSON(data []byte) error {
-	// Try to unmarshal as a string first
-	var s string
-	if err := json.Unmarshal(data, &s); err == nil {
-		*pt = []string{s}
-		return nil
-	}
-
-	// If that fails, try to unmarshal as an array of strings
-	var a []string
-	if err := json.Unmarshal(data, &a); err != nil {
-		return err
-	}
-	*pt = a
-	return nil
-}
-
-// MarshalJSON implements the json.Marshaler interface
-func (pt PropertyType) MarshalJSON() ([]byte, error) {
-	if len(pt) == 1 {
-		// If there's only one type, marshal as a string
-		return json.Marshal(pt[0])
-	}
-	// Otherwise marshal as an array
-	return json.Marshal([]string(pt))
-}
-
-// String returns a string representation of the PropertyType
-func (pt PropertyType) String() string {
-	if len(pt) == 0 {
-		return ""
-	}
-	if len(pt) == 1 {
-		return pt[0]
-	}
-	return fmt.Sprintf("%v", []string(pt))
-}
-
-type ToolProperty struct {
-	AnyOf       []ToolProperty `json:"anyOf,omitempty"`
-	Type        PropertyType   `json:"type"`
-	Items       any            `json:"items,omitempty"`
-	Description string         `json:"description"`
-	Enum        []any          `json:"enum,omitempty"`
-}
-
-// ToTypeScriptType converts a ToolProperty to a TypeScript type string
-func (tp ToolProperty) ToTypeScriptType() string {
-	if len(tp.AnyOf) > 0 {
-		var types []string
-		for _, anyOf := range tp.AnyOf {
-			types = append(types, anyOf.ToTypeScriptType())
-		}
-		return strings.Join(types, " | ")
-	}
-
-	if len(tp.Type) == 0 {
-		return "any"
-	}
-
-	if len(tp.Type) == 1 {
-		return mapToTypeScriptType(tp.Type[0])
-	}
-
-	var types []string
-	for _, t := range tp.Type {
-		types = append(types, mapToTypeScriptType(t))
-	}
-	return strings.Join(types, " | ")
-}
-
-// mapToTypeScriptType maps JSON Schema types to TypeScript types
-func mapToTypeScriptType(jsonType string) string {
-	switch jsonType {
-	case "string":
-		return "string"
-	case "number", "integer":
-		return "number"
-	case "boolean":
-		return "boolean"
-	case "array":
-		return "any[]"
-	case "object":
-		return "Record<string, any>"
-	case "null":
-		return "null"
-	default:
-		return "any"
-	}
-}
-
-type ToolFunctionParameters struct {
-	Type       string                  `json:"type"`
-	Defs       any                     `json:"$defs,omitempty"`
-	Items      any                     `json:"items,omitempty"`
-	Required   []string                `json:"required"`
-	Properties map[string]ToolProperty `json:"properties"`
-}
-
-func (t *ToolFunctionParameters) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
-}
-
 type ToolFunction struct {
-	Name        string                 `json:"name"`
-	Description string                 `json:"description"`
-	Parameters  ToolFunctionParameters `json:"parameters"`
+	Name        string `json:"name"`
+	Description string `json:"description"`
+	Parameters  struct {
+		Type       string   `json:"type"`
+		Required   []string `json:"required"`
+		Properties map[string]struct {
+			Type        string   `json:"type"`
+			Description string   `json:"description"`
+			Enum        []string `json:"enum,omitempty"`
+		} `json:"properties"`
+	} `json:"parameters"`
 }
 
 func (t *ToolFunction) String() string {
@@ -323,19 +194,6 @@ type ChatResponse struct {
 	Metrics
 }
 
-// DebugInfo contains debug information for template rendering
-type DebugInfo struct {
-	RenderedTemplate string `json:"rendered_template"`
-	ImageCount       int    `json:"image_count,omitempty"`
-}
-
-// DebugTemplateResponse is returned when _debug_render_only is set to true
-type DebugTemplateResponse struct {
-	Model     string    `json:"model"`
-	CreatedAt time.Time `json:"created_at"`
-	DebugInfo DebugInfo `json:"_debug_info"`
-}
-
 type Metrics struct {
 	TotalDuration      time.Duration `json:"total_duration,omitempty"`
 	LoadDuration       time.Duration `json:"load_duration,omitempty"`
@@ -345,8 +203,8 @@ type Metrics struct {
 	EvalDuration       time.Duration `json:"eval_duration,omitempty"`
 }
 
-// Options specified in [GenerateRequest].  If you add a new option here, also
-// add it to the API docs.
+// Options specified in [GenerateRequest], if you add a new option here add it
+// to the API docs also.
 type Options struct {
 	Runner
 
@@ -357,12 +215,17 @@ type Options struct {
 	TopK             int      `json:"top_k,omitempty"`
 	TopP             float32  `json:"top_p,omitempty"`
 	MinP             float32  `json:"min_p,omitempty"`
+	TFSZ             float32  `json:"tfs_z,omitempty"`
 	TypicalP         float32  `json:"typical_p,omitempty"`
 	RepeatLastN      int      `json:"repeat_last_n,omitempty"`
 	Temperature      float32  `json:"temperature,omitempty"`
 	RepeatPenalty    float32  `json:"repeat_penalty,omitempty"`
 	PresencePenalty  float32  `json:"presence_penalty,omitempty"`
 	FrequencyPenalty float32  `json:"frequency_penalty,omitempty"`
+	Mirostat         int      `json:"mirostat,omitempty"`
+	MirostatTau      float32  `json:"mirostat_tau,omitempty"`
+	MirostatEta      float32  `json:"mirostat_eta,omitempty"`
+	PenalizeNewline  bool     `json:"penalize_newline,omitempty"`
 	Stop             []string `json:"stop,omitempty"`
 }
 
@@ -372,7 +235,12 @@ type Runner struct {
 	NumBatch  int   `json:"num_batch,omitempty"`
 	NumGPU    int   `json:"num_gpu,omitempty"`
 	MainGPU   int   `json:"main_gpu,omitempty"`
+	LowVRAM   bool  `json:"low_vram,omitempty"`
+	F16KV     bool  `json:"f16_kv,omitempty"`
+	LogitsAll bool  `json:"logits_all,omitempty"`
+	VocabOnly bool  `json:"vocab_only,omitempty"`
 	UseMMap   *bool `json:"use_mmap,omitempty"`
+	UseMLock  bool  `json:"use_mlock,omitempty"`
 	NumThread int   `json:"num_thread,omitempty"`
 }
 
@@ -388,14 +256,10 @@ type EmbedRequest struct {
 	// this request.
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
-	// Truncate truncates the input to fit the model's max sequence length.
 	Truncate *bool `json:"truncate,omitempty"`
 
-	// Dimensions truncates the output embedding to the specified dimension.
-	Dimensions int `json:"dimensions,omitempty"`
-
 	// Options lists model-specific options.
-	Options map[string]any `json:"options"`
+	Options map[string]interface{} `json:"options"`
 }
 
 // EmbedResponse is the response from [Client.Embed].
@@ -421,7 +285,7 @@ type EmbeddingRequest struct {
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]any `json:"options"`
+	Options map[string]interface{} `json:"options"`
 }
 
 // EmbeddingResponse is the response from [Client.Embeddings].
@@ -431,21 +295,17 @@ type EmbeddingResponse struct {
 
 // CreateRequest is the request passed to [Client.Create].
 type CreateRequest struct {
-	Model    string `json:"model"`
-	Stream   *bool  `json:"stream,omitempty"`
-	Quantize string `json:"quantize,omitempty"`
-
-	From       string            `json:"from,omitempty"`
-	Files      map[string]string `json:"files,omitempty"`
-	Adapters   map[string]string `json:"adapters,omitempty"`
-	Template   string            `json:"template,omitempty"`
-	License    any               `json:"license,omitempty"`
-	System     string            `json:"system,omitempty"`
-	Parameters map[string]any    `json:"parameters,omitempty"`
-	Messages   []Message         `json:"messages,omitempty"`
+	Model     string `json:"model"`
+	Modelfile string `json:"modelfile"`
+	Stream    *bool  `json:"stream,omitempty"`
+	Quantize  string `json:"quantize,omitempty"`
 
 	// Deprecated: set the model name with Model instead
 	Name string `json:"name"`
+
+	// Deprecated: set the file content with Modelfile instead
+	Path string `json:"path"`
+
 	// Deprecated: use Quantize instead
 	Quantization string `json:"quantization,omitempty"`
 }
@@ -467,7 +327,7 @@ type ShowRequest struct {
 	Template string `json:"template"`
 	Verbose  bool   `json:"verbose"`
 
-	Options map[string]any `json:"options"`
+	Options map[string]interface{} `json:"options"`
 
 	// Deprecated: set the model name with Model instead
 	Name string `json:"name"`
@@ -475,18 +335,16 @@ type ShowRequest struct {
 
 // ShowResponse is the response returned from [Client.Show].
 type ShowResponse struct {
-	License       string             `json:"license,omitempty"`
-	Modelfile     string             `json:"modelfile,omitempty"`
-	Parameters    string             `json:"parameters,omitempty"`
-	Template      string             `json:"template,omitempty"`
-	System        string             `json:"system,omitempty"`
-	Details       ModelDetails       `json:"details,omitempty"`
-	Messages      []Message          `json:"messages,omitempty"`
-	ModelInfo     map[string]any     `json:"model_info,omitempty"`
-	ProjectorInfo map[string]any     `json:"projector_info,omitempty"`
-	Tensors       []Tensor           `json:"tensors,omitempty"`
-	Capabilities  []model.Capability `json:"capabilities,omitempty"`
-	ModifiedAt    time.Time          `json:"modified_at,omitempty"`
+	License       string         `json:"license,omitempty"`
+	Modelfile     string         `json:"modelfile,omitempty"`
+	Parameters    string         `json:"parameters,omitempty"`
+	Template      string         `json:"template,omitempty"`
+	System        string         `json:"system,omitempty"`
+	Details       ModelDetails   `json:"details,omitempty"`
+	Messages      []Message      `json:"messages,omitempty"`
+	ModelInfo     map[string]any `json:"model_info,omitempty"`
+	ProjectorInfo map[string]any `json:"projector_info,omitempty"`
+	ModifiedAt    time.Time      `json:"modified_at,omitempty"`
 }
 
 // CopyRequest is the request passed to [Client.Copy].
@@ -498,9 +356,9 @@ type CopyRequest struct {
 // PullRequest is the request passed to [Client.Pull].
 type PullRequest struct {
 	Model    string `json:"model"`
-	Insecure bool   `json:"insecure,omitempty"` // Deprecated: ignored
-	Username string `json:"username"`           // Deprecated: ignored
-	Password string `json:"password"`           // Deprecated: ignored
+	Insecure bool   `json:"insecure,omitempty"`
+	Username string `json:"username"`
+	Password string `json:"password"`
 	Stream   *bool  `json:"stream,omitempty"`
 
 	// Deprecated: set the model name with Model instead
@@ -550,14 +408,20 @@ type ListModelResponse struct {
 
 // ProcessModelResponse is a single model description in [ProcessResponse].
 type ProcessModelResponse struct {
-	Name          string       `json:"name"`
-	Model         string       `json:"model"`
-	Size          int64        `json:"size"`
-	Digest        string       `json:"digest"`
-	Details       ModelDetails `json:"details,omitempty"`
-	ExpiresAt     time.Time    `json:"expires_at"`
-	SizeVRAM      int64        `json:"size_vram"`
-	ContextLength int          `json:"context_length"`
+	Name      string       `json:"name"`
+	Model     string       `json:"model"`
+	Size      int64        `json:"size"`
+	Digest    string       `json:"digest"`
+	Details   ModelDetails `json:"details,omitempty"`
+	ExpiresAt time.Time    `json:"expires_at"`
+	SizeVRAM  int64        `json:"size_vram"`
+}
+
+type RetrieveModelResponse struct {
+	Id      string `json:"id"`
+	Object  string `json:"object"`
+	Created int64  `json:"created"`
+	OwnedBy string `json:"owned_by"`
 }
 
 type TokenResponse struct {
@@ -575,10 +439,6 @@ type GenerateResponse struct {
 	// Response is the textual response itself.
 	Response string `json:"response"`
 
-	// Thinking contains the text that was inside thinking tags in the
-	// original model output when ChatRequest.Think is enabled.
-	Thinking string `json:"thinking,omitempty"`
-
 	// Done specifies if the response is complete.
 	Done bool `json:"done"`
 
@@ -590,8 +450,6 @@ type GenerateResponse struct {
 	Context []int `json:"context,omitempty"`
 
 	Metrics
-
-	ToolCalls []ToolCall `json:"tool_calls,omitempty"`
 }
 
 // ModelDetails provides details about a model.
@@ -604,13 +462,6 @@ type ModelDetails struct {
 	QuantizationLevel string   `json:"quantization_level"`
 }
 
-// Tensor describes the metadata for a given tensor.
-type Tensor struct {
-	Name  string   `json:"name"`
-	Type  string   `json:"type"`
-	Shape []uint64 `json:"shape"`
-}
-
 func (m *Metrics) Summary() {
 	if m.TotalDuration > 0 {
 		fmt.Fprintf(os.Stderr, "total duration:       %v\n", m.TotalDuration)
@@ -639,7 +490,7 @@ func (m *Metrics) Summary() {
 	}
 }
 
-func (opts *Options) FromMap(m map[string]any) error {
+func (opts *Options) FromMap(m map[string]interface{}) error {
 	valueOpts := reflect.ValueOf(opts).Elem() // names of the fields in the options struct
 	typeOpts := reflect.TypeOf(opts).Elem()   // types of the fields in the options struct
 
@@ -696,12 +547,12 @@ func (opts *Options) FromMap(m map[string]any) error {
 				}
 				field.SetString(val)
 			case reflect.Slice:
-				// JSON unmarshals to []any, not []string
-				val, ok := val.([]any)
+				// JSON unmarshals to []interface{}, not []string
+				val, ok := val.([]interface{})
 				if !ok {
 					return fmt.Errorf("option %q must be of type array", key)
 				}
-				// convert []any to []string
+				// convert []interface{} to []string
 				slice := make([]string, len(val))
 				for i, item := range val {
 					str, ok := item.(string)
@@ -743,131 +594,32 @@ func DefaultOptions() Options {
 		Temperature:      0.8,
 		TopK:             40,
 		TopP:             0.9,
+		TFSZ:             1.0,
 		TypicalP:         1.0,
 		RepeatLastN:      64,
 		RepeatPenalty:    1.1,
 		PresencePenalty:  0.0,
 		FrequencyPenalty: 0.0,
+		Mirostat:         0,
+		MirostatTau:      5.0,
+		MirostatEta:      0.1,
+		PenalizeNewline:  true,
 		Seed:             -1,
 
 		Runner: Runner{
 			// options set when the model is loaded
-			NumCtx:    int(envconfig.ContextLength()),
+			NumCtx:    2048,
 			NumBatch:  512,
 			NumGPU:    -1, // -1 here indicates that NumGPU should be set dynamically
 			NumThread: 0,  // let the runtime decide
+			LowVRAM:   false,
+			F16KV:     true,
+			UseMLock:  false,
 			UseMMap:   nil,
 		},
 	}
 }
 
-// ThinkValue represents a value that can be a boolean or a string ("high", "medium", "low")
-type ThinkValue struct {
-	// Value can be a bool or string
-	Value interface{}
-}
-
-// IsValid checks if the ThinkValue is valid
-func (t *ThinkValue) IsValid() bool {
-	if t == nil || t.Value == nil {
-		return true // nil is valid (means not set)
-	}
-
-	switch v := t.Value.(type) {
-	case bool:
-		return true
-	case string:
-		return v == "high" || v == "medium" || v == "low"
-	default:
-		return false
-	}
-}
-
-// IsBool returns true if the value is a boolean
-func (t *ThinkValue) IsBool() bool {
-	if t == nil || t.Value == nil {
-		return false
-	}
-	_, ok := t.Value.(bool)
-	return ok
-}
-
-// IsString returns true if the value is a string
-func (t *ThinkValue) IsString() bool {
-	if t == nil || t.Value == nil {
-		return false
-	}
-	_, ok := t.Value.(string)
-	return ok
-}
-
-// Bool returns the value as a bool (true if enabled in any way)
-func (t *ThinkValue) Bool() bool {
-	if t == nil || t.Value == nil {
-		return false
-	}
-
-	switch v := t.Value.(type) {
-	case bool:
-		return v
-	case string:
-		// Any string value ("high", "medium", "low") means thinking is enabled
-		return v == "high" || v == "medium" || v == "low"
-	default:
-		return false
-	}
-}
-
-// String returns the value as a string
-func (t *ThinkValue) String() string {
-	if t == nil || t.Value == nil {
-		return ""
-	}
-
-	switch v := t.Value.(type) {
-	case string:
-		return v
-	case bool:
-		if v {
-			return "medium" // Default level when just true
-		}
-		return ""
-	default:
-		return ""
-	}
-}
-
-// UnmarshalJSON implements json.Unmarshaler
-func (t *ThinkValue) UnmarshalJSON(data []byte) error {
-	// Try to unmarshal as bool first
-	var b bool
-	if err := json.Unmarshal(data, &b); err == nil {
-		t.Value = b
-		return nil
-	}
-
-	// Try to unmarshal as string
-	var s string
-	if err := json.Unmarshal(data, &s); err == nil {
-		// Validate string values
-		if s != "high" && s != "medium" && s != "low" {
-			return fmt.Errorf("invalid think value: %q (must be \"high\", \"medium\", \"low\", true, or false)", s)
-		}
-		t.Value = s
-		return nil
-	}
-
-	return fmt.Errorf("think must be a boolean or string (\"high\", \"medium\", \"low\")")
-}
-
-// MarshalJSON implements json.Marshaler
-func (t *ThinkValue) MarshalJSON() ([]byte, error) {
-	if t == nil || t.Value == nil {
-		return []byte("null"), nil
-	}
-	return json.Marshal(t.Value)
-}
-
 type Duration struct {
 	time.Duration
 }
@@ -892,7 +644,7 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
 		if t < 0 {
 			d.Duration = time.Duration(math.MaxInt64)
 		} else {
-			d.Duration = time.Duration(t * float64(time.Second))
+			d.Duration = time.Duration(int(t) * int(time.Second))
 		}
 	case string:
 		d.Duration, err = time.ParseDuration(t)
@@ -910,7 +662,7 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
 }
 
 // FormatParams converts specified parameter options to their correct types
-func FormatParams(params map[string][]string) (map[string]any, error) {
+func FormatParams(params map[string][]string) (map[string]interface{}, error) {
 	opts := Options{}
 	valueOpts := reflect.ValueOf(&opts).Elem() // names of the fields in the options struct
 	typeOpts := reflect.TypeOf(opts)           // types of the fields in the options struct
@@ -924,7 +676,7 @@ func FormatParams(params map[string][]string) (map[string]any, error) {
 		}
 	}
 
-	out := make(map[string]any)
+	out := make(map[string]interface{})
 	// iterate params and set values based on json struct tags
 	for key, vals := range params {
 		if opt, ok := jsonOpts[key]; !ok {

api/types_test.go

@@ -17,11 +17,6 @@ func TestKeepAliveParsingFromJSON(t *testing.T) {
 		req  string
 		exp  *Duration
 	}{
-		{
-			name: "Unset",
-			req:  `{ }`,
-			exp:  nil,
-		},
 		{
 			name: "Positive Integer",
 			req:  `{ "keep_alive": 42 }`,
@@ -30,7 +25,7 @@ func TestKeepAliveParsingFromJSON(t *testing.T) {
 		{
 			name: "Positive Float",
 			req:  `{ "keep_alive": 42.5 }`,
-			exp:  &Duration{42500 * time.Millisecond},
+			exp:  &Duration{42 * time.Second},
 		},
 		{
 			name: "Positive Integer String",
@@ -139,7 +134,7 @@ func TestUseMmapParsingFromJSON(t *testing.T) {
 
 	for _, test := range tests {
 		t.Run(test.name, func(t *testing.T) {
-			var oMap map[string]any
+			var oMap map[string]interface{}
 			err := json.Unmarshal([]byte(test.req), &oMap)
 			require.NoError(t, err)
 			opts := DefaultOptions()
@@ -236,255 +231,3 @@ func TestMessage_UnmarshalJSON(t *testing.T) {
 		}
 	}
 }
-
-func TestToolFunction_UnmarshalJSON(t *testing.T) {
-	tests := []struct {
-		name    string
-		input   string
-		wantErr string
-	}{
-		{
-			name: "valid enum with same types",
-			input: `{
-				"name": "test",
-				"description": "test function",
-				"parameters": {
-					"type": "object",
-					"required": ["test"],
-					"properties": {
-						"test": {
-							"type": "string",
-							"description": "test prop",
-							"enum": ["a", "b", "c"]
-						}
-					}
-				}
-			}`,
-			wantErr: "",
-		},
-		{
-			name: "empty enum array",
-			input: `{
-				"name": "test",
-				"description": "test function",
-				"parameters": {
-					"type": "object",
-					"required": ["test"],
-					"properties": {
-						"test": {
-							"type": "string",
-							"description": "test prop",
-							"enum": []
-						}
-					}
-				}
-			}`,
-			wantErr: "",
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			var tf ToolFunction
-			err := json.Unmarshal([]byte(tt.input), &tf)
-
-			if tt.wantErr != "" {
-				require.Error(t, err)
-				assert.Contains(t, err.Error(), tt.wantErr)
-			} else {
-				require.NoError(t, err)
-			}
-		})
-	}
-}
-
-func TestPropertyType_UnmarshalJSON(t *testing.T) {
-	tests := []struct {
-		name     string
-		input    string
-		expected PropertyType
-	}{
-		{
-			name:     "string type",
-			input:    `"string"`,
-			expected: PropertyType{"string"},
-		},
-		{
-			name:     "array of types",
-			input:    `["string", "number"]`,
-			expected: PropertyType{"string", "number"},
-		},
-		{
-			name:     "array with single type",
-			input:    `["string"]`,
-			expected: PropertyType{"string"},
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			var pt PropertyType
-			if err := json.Unmarshal([]byte(test.input), &pt); err != nil {
-				t.Errorf("Unexpected error: %v", err)
-			}
-
-			if len(pt) != len(test.expected) {
-				t.Errorf("Length mismatch: got %v, expected %v", len(pt), len(test.expected))
-			}
-
-			for i, v := range pt {
-				if v != test.expected[i] {
-					t.Errorf("Value mismatch at index %d: got %v, expected %v", i, v, test.expected[i])
-				}
-			}
-		})
-	}
-}
-
-func TestPropertyType_MarshalJSON(t *testing.T) {
-	tests := []struct {
-		name     string
-		input    PropertyType
-		expected string
-	}{
-		{
-			name:     "single type",
-			input:    PropertyType{"string"},
-			expected: `"string"`,
-		},
-		{
-			name:     "multiple types",
-			input:    PropertyType{"string", "number"},
-			expected: `["string","number"]`,
-		},
-		{
-			name:     "empty type",
-			input:    PropertyType{},
-			expected: `[]`,
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			data, err := json.Marshal(test.input)
-			if err != nil {
-				t.Errorf("Unexpected error: %v", err)
-			}
-
-			if string(data) != test.expected {
-				t.Errorf("Marshaled data mismatch: got %v, expected %v", string(data), test.expected)
-			}
-		})
-	}
-}
-
-func TestThinking_UnmarshalJSON(t *testing.T) {
-	tests := []struct {
-		name             string
-		input            string
-		expectedThinking *ThinkValue
-		expectedError    bool
-	}{
-		{
-			name:             "true",
-			input:            `{ "think": true }`,
-			expectedThinking: &ThinkValue{Value: true},
-		},
-		{
-			name:             "false",
-			input:            `{ "think": false }`,
-			expectedThinking: &ThinkValue{Value: false},
-		},
-		{
-			name:             "unset",
-			input:            `{ }`,
-			expectedThinking: nil,
-		},
-		{
-			name:             "string_high",
-			input:            `{ "think": "high" }`,
-			expectedThinking: &ThinkValue{Value: "high"},
-		},
-		{
-			name:             "string_medium",
-			input:            `{ "think": "medium" }`,
-			expectedThinking: &ThinkValue{Value: "medium"},
-		},
-		{
-			name:             "string_low",
-			input:            `{ "think": "low" }`,
-			expectedThinking: &ThinkValue{Value: "low"},
-		},
-		{
-			name:             "invalid_string",
-			input:            `{ "think": "invalid" }`,
-			expectedThinking: nil,
-			expectedError:    true,
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			var req GenerateRequest
-			err := json.Unmarshal([]byte(test.input), &req)
-			if test.expectedError {
-				require.Error(t, err)
-			} else {
-				require.NoError(t, err)
-				if test.expectedThinking == nil {
-					assert.Nil(t, req.Think)
-				} else {
-					require.NotNil(t, req.Think)
-					assert.Equal(t, test.expectedThinking.Value, req.Think.Value)
-				}
-			}
-		})
-	}
-}
-
-func TestToolFunctionParameters_String(t *testing.T) {
-	tests := []struct {
-		name     string
-		params   ToolFunctionParameters
-		expected string
-	}{
-		{
-			name: "simple object with string property",
-			params: ToolFunctionParameters{
-				Type:     "object",
-				Required: []string{"name"},
-				Properties: map[string]ToolProperty{
-					"name": {
-						Type:        PropertyType{"string"},
-						Description: "The name of the person",
-					},
-				},
-			},
-			expected: `{"type":"object","required":["name"],"properties":{"name":{"type":"string","description":"The name of the person"}}}`,
-		},
-		{
-			name: "marshal failure returns empty string",
-			params: ToolFunctionParameters{
-				Type: "object",
-				Defs: func() any {
-					// Create a cycle that will cause json.Marshal to fail
-					type selfRef struct {
-						Self *selfRef
-					}
-					s := &selfRef{}
-					s.Self = s
-					return s
-				}(),
-				Properties: map[string]ToolProperty{},
-			},
-			expected: "",
-		},
-	}
-
-	for _, test := range tests {
-		t.Run(test.name, func(t *testing.T) {
-			result := test.params.String()
-			assert.Equal(t, test.expected, result)
-		})
-	}
-}

api/types_typescript_test.go

@@ -1,142 +0,0 @@
-package api
-
-import (
-	"testing"
-)
-
-func TestToolParameterToTypeScriptType(t *testing.T) {
-	tests := []struct {
-		name     string
-		param    ToolProperty
-		expected string
-	}{
-		{
-			name: "single string type",
-			param: ToolProperty{
-				Type: PropertyType{"string"},
-			},
-			expected: "string",
-		},
-		{
-			name: "single number type",
-			param: ToolProperty{
-				Type: PropertyType{"number"},
-			},
-			expected: "number",
-		},
-		{
-			name: "integer maps to number",
-			param: ToolProperty{
-				Type: PropertyType{"integer"},
-			},
-			expected: "number",
-		},
-		{
-			name: "boolean type",
-			param: ToolProperty{
-				Type: PropertyType{"boolean"},
-			},
-			expected: "boolean",
-		},
-		{
-			name: "array type",
-			param: ToolProperty{
-				Type: PropertyType{"array"},
-			},
-			expected: "any[]",
-		},
-		{
-			name: "object type",
-			param: ToolProperty{
-				Type: PropertyType{"object"},
-			},
-			expected: "Record<string, any>",
-		},
-		{
-			name: "null type",
-			param: ToolProperty{
-				Type: PropertyType{"null"},
-			},
-			expected: "null",
-		},
-		{
-			name: "multiple types as union",
-			param: ToolProperty{
-				Type: PropertyType{"string", "number"},
-			},
-			expected: "string | number",
-		},
-		{
-			name: "string or null union",
-			param: ToolProperty{
-				Type: PropertyType{"string", "null"},
-			},
-			expected: "string | null",
-		},
-		{
-			name: "anyOf with single types",
-			param: ToolProperty{
-				AnyOf: []ToolProperty{
-					{Type: PropertyType{"string"}},
-					{Type: PropertyType{"number"}},
-				},
-			},
-			expected: "string | number",
-		},
-		{
-			name: "anyOf with multiple types in each branch",
-			param: ToolProperty{
-				AnyOf: []ToolProperty{
-					{Type: PropertyType{"string", "null"}},
-					{Type: PropertyType{"number"}},
-				},
-			},
-			expected: "string | null | number",
-		},
-		{
-			name: "nested anyOf",
-			param: ToolProperty{
-				AnyOf: []ToolProperty{
-					{Type: PropertyType{"boolean"}},
-					{
-						AnyOf: []ToolProperty{
-							{Type: PropertyType{"string"}},
-							{Type: PropertyType{"number"}},
-						},
-					},
-				},
-			},
-			expected: "boolean | string | number",
-		},
-		{
-			name: "empty type returns any",
-			param: ToolProperty{
-				Type: PropertyType{},
-			},
-			expected: "any",
-		},
-		{
-			name: "unknown type maps to any",
-			param: ToolProperty{
-				Type: PropertyType{"unknown_type"},
-			},
-			expected: "any",
-		},
-		{
-			name: "multiple types including array",
-			param: ToolProperty{
-				Type: PropertyType{"string", "array", "null"},
-			},
-			expected: "string | any[] | null",
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			result := tt.param.ToTypeScriptType()
-			if result != tt.expected {
-				t.Errorf("ToTypeScriptType() = %q, want %q", result, tt.expected)
-			}
-		})
-	}
-}

app/README.md

@@ -17,6 +17,6 @@ If you want to build the installer, youll need to install
 In the top directory of this repo, run the following powershell script
 to build the ollama CLI, ollama app, and ollama installer.
 
-```powershell
+```
 powershell -ExecutionPolicy Bypass -File .\scripts\build_windows.ps1
 ```

app/lifecycle/lifecycle.go

@@ -11,12 +11,10 @@ import (
 
 	"github.com/ollama/ollama/app/store"
 	"github.com/ollama/ollama/app/tray"
-	"github.com/ollama/ollama/envconfig"
 )
 
 func Run() {
 	InitLogging()
-	slog.Info("app config", "env", envconfig.Values())
 
 	ctx, cancel := context.WithCancel(context.Background())
 	var done chan int

app/lifecycle/logging.go

@@ -4,14 +4,20 @@ import (
 	"fmt"
 	"log/slog"
 	"os"
+	"path/filepath"
 	"strconv"
 	"strings"
 
 	"github.com/ollama/ollama/envconfig"
-	"github.com/ollama/ollama/logutil"
 )
 
 func InitLogging() {
+	level := slog.LevelInfo
+
+	if envconfig.Debug() {
+		level = slog.LevelDebug
+	}
+
 	var logFile *os.File
 	var err error
 	// Detect if we're a GUI app on windows, and if not, send logs to console
@@ -27,8 +33,20 @@ func InitLogging() {
 			return
 		}
 	}
+	handler := slog.NewTextHandler(logFile, &slog.HandlerOptions{
+		Level:     level,
+		AddSource: true,
+		ReplaceAttr: func(_ []string, attr slog.Attr) slog.Attr {
+			if attr.Key == slog.SourceKey {
+				source := attr.Value.Any().(*slog.Source)
+				source.File = filepath.Base(source.File)
+			}
+			return attr
+		},
+	})
+
+	slog.SetDefault(slog.New(handler))
 
-	slog.SetDefault(logutil.NewLogger(logFile, envconfig.LogLevel()))
 	slog.Info("ollama app started")
 }
 

app/lifecycle/paths.go

@@ -36,13 +36,8 @@ func init() {
 		ServerLogFile = filepath.Join(AppDataDir, "server.log")
 		UpgradeLogFile = filepath.Join(AppDataDir, "upgrade.log")
 
-		exe, err := os.Executable()
-		if err != nil {
-			slog.Warn("error discovering executable directory", "error", err)
-			AppDir = filepath.Join(localAppData, "Programs", "Ollama")
-		} else {
-			AppDir = filepath.Dir(exe)
-		}
+		// Executables are stored in APPDATA
+		AppDir = filepath.Join(localAppData, "Programs", "Ollama")
 
 		// Make sure we have PATH set correctly for any spawned children
 		paths := strings.Split(os.Getenv("PATH"), ";")
@@ -69,7 +64,7 @@ func init() {
 		}
 
 		// Make sure our logging dir exists
-		_, err = os.Stat(AppDataDir)
+		_, err := os.Stat(AppDataDir)
 		if errors.Is(err, os.ErrNotExist) {
 			if err := os.MkdirAll(AppDataDir, 0o755); err != nil {
 				slog.Error(fmt.Sprintf("create ollama dir %s: %v", AppDataDir, err))

app/lifecycle/server.go

@@ -18,17 +18,11 @@ func getCLIFullPath(command string) string {
 	var cmdPath string
 	appExe, err := os.Executable()
 	if err == nil {
-		// Check both the same location as the tray app, as well as ./bin
 		cmdPath = filepath.Join(filepath.Dir(appExe), command)
 		_, err := os.Stat(cmdPath)
 		if err == nil {
 			return cmdPath
 		}
-		cmdPath = filepath.Join(filepath.Dir(appExe), "bin", command)
-		_, err = os.Stat(cmdPath)
-		if err == nil {
-			return cmdPath
-		}
 	}
 	cmdPath, err = exec.LookPath(command)
 	if err == nil {

app/lifecycle/updater_windows.go

@@ -26,15 +26,19 @@ func DoUpgrade(cancel context.CancelFunc, done chan int) error {
 	slog.Info("starting upgrade with " + installerExe)
 	slog.Info("upgrade log file " + UpgradeLogFile)
 
-	// make the upgrade show progress, but non interactive
+	// When running in debug mode, we'll be "verbose" and let the installer pop up and prompt
 	installArgs := []string{
 		"/CLOSEAPPLICATIONS",                    // Quit the tray app if it's still running
 		"/LOG=" + filepath.Base(UpgradeLogFile), // Only relative seems reliable, so set pwd
 		"/FORCECLOSEAPPLICATIONS",               // Force close the tray app - might be needed
-		"/SP",                                   // Skip the "This will install... Do you wish to continue" prompt
-		"/NOCANCEL",                             // Disable the ability to cancel upgrade mid-flight to avoid partially installed upgrades
-		"/SILENT",
 	}
+	// make the upgrade as quiet as possible (no GUI, no prompts)
+	installArgs = append(installArgs,
+		"/SP", // Skip the "This will install... Do you wish to continue" prompt
+		"/SUPPRESSMSGBOXES",
+		"/SILENT",
+		"/VERYSILENT",
+	)
 
 	// Safeguard in case we have requests in flight that need to drain...
 	slog.Info("Waiting for server to shutdown")

app/ollama.iss

@@ -53,8 +53,8 @@ RestartIfNeededByRun=no
 ; https://jrsoftware.org/ishelp/index.php?topic=setup_wizardimagefile
 WizardSmallImageFile=.\assets\setup.bmp
 
-; Ollama requires Windows 10 22H2 or newer for proper unicode rendering
-; TODO: consider setting this to 10.0.19045
+; TODO verifty actual min windows version...
+; OG Win 10
 MinVersion=10.0.10240
 
 ; First release that supports WinRT UI Composition for win32 apps
@@ -97,6 +97,7 @@ Source: "..\dist\windows-amd64\lib\ollama\*"; DestDir: "{app}\lib\ollama\"; Chec
 Source: "..\dist\windows-arm64\vc_redist.arm64.exe"; DestDir: "{tmp}"; Check: IsArm64() and vc_redist_needed(); Flags: deleteafterinstall
 Source: "..\dist\windows-arm64-app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ;Check: IsArm64();  Flags: ignoreversion 64bit
 Source: "..\dist\windows-arm64\ollama.exe"; DestDir: "{app}"; Check: IsArm64(); Flags: ignoreversion 64bit
+Source: "..\dist\windows-arm64\lib\ollama\*"; DestDir: "{app}\lib\ollama\"; Check: IsArm64(); Flags: ignoreversion 64bit recursesubdirs
 #endif
 
 Source: "..\dist\ollama_welcome.ps1"; DestDir: "{app}"; Flags: ignoreversion
@@ -135,7 +136,7 @@ Type: filesandordirs; Name: "{%TEMP}\ollama*"
 Type: filesandordirs; Name: "{%LOCALAPPDATA}\Programs\Ollama"
 
 [Messages]
-WizardReady=Ollama
+WizardReady=Ollama Windows Preview
 ReadyLabel1=%nLet's get you up and running with your own large language models.
 SetupAppRunningError=Another Ollama installer is running.%n%nPlease cancel or finish the other installer, then click OK to continue with this install, or Cancel to exit.
 

app/store/store.go

@@ -64,7 +64,7 @@ func initStore() {
 		slog.Debug(fmt.Sprintf("unexpected error searching for store: %s", err))
 	}
 	slog.Debug("initializing new store")
-	store.ID = uuid.NewString()
+	store.ID = uuid.New().String()
 	writeStore(getStorePath())
 }
 

app/tray/wintray/eventloop.go

@@ -98,7 +98,7 @@ func (t *winTray) wndProc(hWnd windows.Handle, message uint32, wParam, lParam ui
 		}
 		err = t.wcex.unregister()
 		if err != nil {
-			slog.Error(fmt.Sprintf("failed to unregister window %s", err))
+			slog.Error(fmt.Sprintf("failed to uregister windo %s", err))
 		}
 	case WM_DESTROY:
 		// same as WM_ENDSESSION, but throws 0 exit code after all

app/tray/wintray/menus.go

@@ -11,13 +11,12 @@ import (
 )
 
 const (
-	_ = iota
-	updateAvailableMenuID
-	updateMenuID
-	separatorMenuID
-	diagLogsMenuID
-	diagSeparatorMenuID
-	quitMenuID
+	updateAvailableMenuID = 1
+	updateMenuID          = updateAvailableMenuID + 1
+	separatorMenuID       = updateMenuID + 1
+	diagLogsMenuID        = separatorMenuID + 1
+	diagSeparatorMenuID   = diagLogsMenuID + 1
+	quitMenuID            = diagSeparatorMenuID + 1
 )
 
 func (t *winTray) initMenus() error {
@@ -39,7 +38,7 @@ func (t *winTray) UpdateAvailable(ver string) error {
 		if err := t.addOrUpdateMenuItem(updateAvailableMenuID, 0, updateAvailableMenuTitle, true); err != nil {
 			return fmt.Errorf("unable to create menu entries %w", err)
 		}
-		if err := t.addOrUpdateMenuItem(updateMenuID, 0, updateMenuTitle, false); err != nil {
+		if err := t.addOrUpdateMenuItem(updateMenuID, 0, updateMenutTitle, false); err != nil {
 			return fmt.Errorf("unable to create menu entries %w", err)
 		}
 		if err := t.addSeparatorMenuItem(separatorMenuID, 0); err != nil {

app/tray/wintray/messages.go

@@ -10,6 +10,6 @@ const (
 
 	quitMenuTitle            = "Quit Ollama"
 	updateAvailableMenuTitle = "An update is available"
-	updateMenuTitle          = "Restart to update"
+	updateMenutTitle         = "Restart to update"
 	diagLogsMenuTitle        = "View logs"
 )

app/tray/wintray/tray.go

@@ -361,7 +361,7 @@ func (t *winTray) showMenu() error {
 
 	boolRet, _, err = pTrackPopupMenu.Call(
 		uintptr(t.menus[0]),
-		TPM_BOTTOMALIGN|TPM_LEFTALIGN|TPM_RIGHTBUTTON,
+		TPM_BOTTOMALIGN|TPM_LEFTALIGN,
 		uintptr(p.X),
 		uintptr(p.Y),
 		0,

app/tray/wintray/w32api.go

@@ -67,7 +67,6 @@ const (
 	SW_HIDE             = 0
 	TPM_BOTTOMALIGN     = 0x0020
 	TPM_LEFTALIGN       = 0x0000
-	TPM_RIGHTBUTTON     = 0x0002
 	WM_CLOSE            = 0x0010
 	WM_USER             = 0x0400
 	WS_CAPTION          = 0x00C00000

build/darwin/amd64/placeholder

@@ -0,0 +1 @@
+This is here to make sure the build/ directory exists for the go:embed command

build/darwin/arm64/placeholder

@@ -0,0 +1 @@
+This is here to make sure the build/ directory exists for the go:embed command

build/embed_darwin_amd64.go

@@ -0,0 +1,8 @@
+package build
+
+import "embed"
+
+// Darwin payloads separated by architecture to avoid duplicate payloads when cross compiling
+
+//go:embed darwin/amd64/*
+var EmbedFS embed.FS

build/embed_darwin_arm64.go

@@ -0,0 +1,8 @@
+package build
+
+import "embed"
+
+// Darwin payloads separated by architecture to avoid duplicate payloads when cross compiling
+
+//go:embed darwin/arm64/*
+var EmbedFS embed.FS

build/embed_linux.go

@@ -0,0 +1,6 @@
+package build
+
+import "embed"
+
+//go:embed linux/*
+var EmbedFS embed.FS

build/embed_unused.go

@@ -0,0 +1,8 @@
+//go:build !linux && !darwin
+
+package build
+
+import "embed"
+
+// unused on windows
+var EmbedFS embed.FS

build/linux/amd64/placeholder

@@ -0,0 +1 @@
+This is here to make sure the build/ directory exists for the go:embed command

build/linux/arm64/placeholder

@@ -0,0 +1 @@
+This is here to make sure the build/ directory exists for the go:embed command

cmd/cmd_test.go

@@ -2,20 +2,19 @@ package cmd
 
 import (
 	"bytes"
+	"context"
 	"encoding/json"
-	"io"
 	"net/http"
 	"net/http/httptest"
 	"os"
+	"path/filepath"
 	"strings"
 	"testing"
-	"time"
 
 	"github.com/google/go-cmp/cmp"
 	"github.com/spf13/cobra"
 
 	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/types/model"
 )
 
 func TestShowInfo(t *testing.T) {
@@ -27,7 +26,7 @@ func TestShowInfo(t *testing.T) {
 				ParameterSize:     "7B",
 				QuantizationLevel: "FP16",
 			},
-		}, false, &b); err != nil {
+		}, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -57,7 +56,7 @@ func TestShowInfo(t *testing.T) {
 				ParameterSize:     "7B",
 				QuantizationLevel: "FP16",
 			},
-		}, false, &b); err != nil {
+		}, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -68,60 +67,6 @@ func TestShowInfo(t *testing.T) {
     embedding length    0       
     quantization        FP16    
 
-`
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			t.Errorf("unexpected output (-want +got):\n%s", diff)
-		}
-	})
-
-	t.Run("verbose model", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "8B",
-				QuantizationLevel: "FP16",
-			},
-			Parameters: `
-			stop up`,
-			ModelInfo: map[string]any{
-				"general.architecture":    "test",
-				"general.parameter_count": float64(8_000_000_000),
-				"some.true_bool":          true,
-				"some.false_bool":         false,
-				"test.context_length":     float64(1000),
-				"test.embedding_length":   float64(11434),
-			},
-			Tensors: []api.Tensor{
-				{Name: "blk.0.attn_k.weight", Type: "BF16", Shape: []uint64{42, 3117}},
-				{Name: "blk.0.attn_q.weight", Type: "FP16", Shape: []uint64{3117, 42}},
-			},
-		}, true, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture        test     
-    parameters          8B       
-    context length      1000     
-    embedding length    11434    
-    quantization        FP16     
-
-  Parameters
-    stop    up    
-
-  Metadata
-    general.architecture       test     
-    general.parameter_count    8e+09    
-    some.false_bool            false    
-    some.true_bool             true     
-    test.context_length        1000     
-    test.embedding_length      11434    
-
-  Tensors
-    blk.0.attn_k.weight    BF16    [42 3117]    
-    blk.0.attn_q.weight    FP16    [3117 42]    
-
 `
 		if diff := cmp.Diff(expect, b.String()); diff != "" {
 			t.Errorf("unexpected output (-want +got):\n%s", diff)
@@ -143,7 +88,7 @@ func TestShowInfo(t *testing.T) {
 			stop you
 			stop up
 			temperature 99`,
-		}, false, &b); err != nil {
+		}, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -180,7 +125,7 @@ func TestShowInfo(t *testing.T) {
 				"clip.vision.embedding_length": float64(0),
 				"clip.vision.projection_dim":   float64(0),
 			},
-		}, false, &b); err != nil {
+		}, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -213,7 +158,7 @@ func TestShowInfo(t *testing.T) {
 Ahoy, matey!
 Weigh anchor!
 			`,
-		}, false, &b); err != nil {
+		}, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -225,7 +170,6 @@ Weigh anchor!
   System
     You are a pirate!    
     Ahoy, matey!         
-    ...                  
 
 `
 		if diff := cmp.Diff(expect, b.String()); diff != "" {
@@ -235,15 +179,19 @@ Weigh anchor!
 
 	t.Run("license", func(t *testing.T) {
 		var b bytes.Buffer
-		license := "MIT License\nCopyright (c) Ollama\n"
+		license, err := os.ReadFile(filepath.Join("..", "LICENSE"))
+		if err != nil {
+			t.Fatal(err)
+		}
+
 		if err := showInfo(&api.ShowResponse{
 			Details: api.ModelDetails{
 				Family:            "test",
 				ParameterSize:     "7B",
 				QuantizationLevel: "FP16",
 			},
-			License: license,
-		}, false, &b); err != nil {
+			License: string(license),
+		}, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -261,34 +209,6 @@ Weigh anchor!
 			t.Errorf("unexpected output (-want +got):\n%s", diff)
 		}
 	})
-
-	t.Run("capabilities", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-			Capabilities: []model.Capability{model.CapabilityVision, model.CapabilityTools},
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := "  Model\n" +
-			"    architecture    test    \n" +
-			"    parameters      7B      \n" +
-			"    quantization    FP16    \n" +
-			"\n" +
-			"  Capabilities\n" +
-			"    vision    \n" +
-			"    tools     \n" +
-			"\n"
-
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			t.Errorf("unexpected output (-want +got):\n%s", diff)
-		}
-	})
 }
 
 func TestDeleteHandler(t *testing.T) {
@@ -337,7 +257,7 @@ func TestDeleteHandler(t *testing.T) {
 	t.Cleanup(mockServer.Close)
 
 	cmd := &cobra.Command{}
-	cmd.SetContext(t.Context())
+	cmd.SetContext(context.TODO())
 	if err := DeleteHandler(cmd, []string{"test-model"}); err != nil {
 		t.Fatalf("DeleteHandler failed: %v", err)
 	}
@@ -377,7 +297,7 @@ func TestGetModelfileName(t *testing.T) {
 			name:          "modelfile specified, no modelfile exists",
 			modelfileName: "crazyfile",
 			fileExists:    false,
-			expectedName:  "",
+			expectedName:  "crazyfile",
 			expectedErr:   os.ErrNotExist,
 		},
 		{
@@ -399,6 +319,11 @@ func TestGetModelfileName(t *testing.T) {
 			var expectedFilename string
 
 			if tt.fileExists {
+				tempDir, err := os.MkdirTemp("", "modelfiledir")
+				defer os.RemoveAll(tempDir)
+				if err != nil {
+					t.Fatalf("temp modelfile dir creation failed: %v", err)
+				}
 				var fn string
 				if tt.modelfileName != "" {
 					fn = tt.modelfileName
@@ -406,11 +331,10 @@ func TestGetModelfileName(t *testing.T) {
 					fn = "Modelfile"
 				}
 
-				tempFile, err := os.CreateTemp(t.TempDir(), fn)
+				tempFile, err := os.CreateTemp(tempDir, fn)
 				if err != nil {
 					t.Fatalf("temp modelfile creation failed: %v", err)
 				}
-				defer tempFile.Close()
 
 				expectedFilename = tempFile.Name()
 				err = cmd.Flags().Set("file", expectedFilename)
@@ -418,8 +342,8 @@ func TestGetModelfileName(t *testing.T) {
 					t.Fatalf("couldn't set file flag: %v", err)
 				}
 			} else {
-				expectedFilename = tt.expectedName
 				if tt.modelfileName != "" {
+					expectedFilename = tt.modelfileName
 					err := cmd.Flags().Set("file", tt.modelfileName)
 					if err != nil {
 						t.Fatalf("couldn't set file flag: %v", err)
@@ -445,473 +369,3 @@ func TestGetModelfileName(t *testing.T) {
 		})
 	}
 }
-
-func TestPushHandler(t *testing.T) {
-	tests := []struct {
-		name           string
-		modelName      string
-		serverResponse map[string]func(w http.ResponseWriter, r *http.Request)
-		expectedError  string
-		expectedOutput string
-	}{
-		{
-			name:      "successful push",
-			modelName: "test-model",
-			serverResponse: map[string]func(w http.ResponseWriter, r *http.Request){
-				"/api/push": func(w http.ResponseWriter, r *http.Request) {
-					if r.Method != http.MethodPost {
-						t.Errorf("expected POST request, got %s", r.Method)
-					}
-
-					var req api.PushRequest
-					if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
-						http.Error(w, err.Error(), http.StatusBadRequest)
-						return
-					}
-
-					if req.Name != "test-model" {
-						t.Errorf("expected model name 'test-model', got %s", req.Name)
-					}
-
-					// Simulate progress updates
-					responses := []api.ProgressResponse{
-						{Status: "preparing manifest"},
-						{Digest: "sha256:abc123456789", Total: 100, Completed: 50},
-						{Digest: "sha256:abc123456789", Total: 100, Completed: 100},
-					}
-
-					for _, resp := range responses {
-						if err := json.NewEncoder(w).Encode(resp); err != nil {
-							http.Error(w, err.Error(), http.StatusInternalServerError)
-							return
-						}
-						w.(http.Flusher).Flush()
-					}
-				},
-			},
-			expectedOutput: "\nYou can find your model at:\n\n\thttps://ollama.com/test-model\n",
-		},
-		{
-			name:      "unauthorized push",
-			modelName: "unauthorized-model",
-			serverResponse: map[string]func(w http.ResponseWriter, r *http.Request){
-				"/api/push": func(w http.ResponseWriter, r *http.Request) {
-					w.Header().Set("Content-Type", "application/json")
-					w.WriteHeader(http.StatusUnauthorized)
-					err := json.NewEncoder(w).Encode(map[string]string{
-						"error": "access denied",
-					})
-					if err != nil {
-						t.Fatal(err)
-					}
-				},
-			},
-			expectedError: "you are not authorized to push to this namespace, create the model under a namespace you own",
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			mockServer := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-				if handler, ok := tt.serverResponse[r.URL.Path]; ok {
-					handler(w, r)
-					return
-				}
-				http.Error(w, "not found", http.StatusNotFound)
-			}))
-			defer mockServer.Close()
-
-			t.Setenv("OLLAMA_HOST", mockServer.URL)
-
-			cmd := &cobra.Command{}
-			cmd.Flags().Bool("insecure", false, "")
-			cmd.SetContext(t.Context())
-
-			// Redirect stderr to capture progress output
-			oldStderr := os.Stderr
-			r, w, _ := os.Pipe()
-			os.Stderr = w
-
-			// Capture stdout for the "Model pushed" message
-			oldStdout := os.Stdout
-			outR, outW, _ := os.Pipe()
-			os.Stdout = outW
-
-			err := PushHandler(cmd, []string{tt.modelName})
-
-			// Restore stderr
-			w.Close()
-			os.Stderr = oldStderr
-			// drain the pipe
-			if _, err := io.ReadAll(r); err != nil {
-				t.Fatal(err)
-			}
-
-			// Restore stdout and get output
-			outW.Close()
-			os.Stdout = oldStdout
-			stdout, _ := io.ReadAll(outR)
-
-			if tt.expectedError == "" {
-				if err != nil {
-					t.Errorf("expected no error, got %v", err)
-				}
-				if tt.expectedOutput != "" {
-					if got := string(stdout); got != tt.expectedOutput {
-						t.Errorf("expected output %q, got %q", tt.expectedOutput, got)
-					}
-				}
-			} else {
-				if err == nil || !strings.Contains(err.Error(), tt.expectedError) {
-					t.Errorf("expected error containing %q, got %v", tt.expectedError, err)
-				}
-			}
-		})
-	}
-}
-
-func TestListHandler(t *testing.T) {
-	tests := []struct {
-		name           string
-		args           []string
-		serverResponse []api.ListModelResponse
-		expectedError  string
-		expectedOutput string
-	}{
-		{
-			name: "list all models",
-			args: []string{},
-			serverResponse: []api.ListModelResponse{
-				{Name: "model1", Digest: "sha256:abc123", Size: 1024, ModifiedAt: time.Now().Add(-24 * time.Hour)},
-				{Name: "model2", Digest: "sha256:def456", Size: 2048, ModifiedAt: time.Now().Add(-48 * time.Hour)},
-			},
-			expectedOutput: "NAME      ID              SIZE      MODIFIED     \n" +
-				"model1    sha256:abc12    1.0 KB    24 hours ago    \n" +
-				"model2    sha256:def45    2.0 KB    2 days ago      \n",
-		},
-		{
-			name: "filter models by prefix",
-			args: []string{"model1"},
-			serverResponse: []api.ListModelResponse{
-				{Name: "model1", Digest: "sha256:abc123", Size: 1024, ModifiedAt: time.Now().Add(-24 * time.Hour)},
-				{Name: "model2", Digest: "sha256:def456", Size: 2048, ModifiedAt: time.Now().Add(-24 * time.Hour)},
-			},
-			expectedOutput: "NAME      ID              SIZE      MODIFIED     \n" +
-				"model1    sha256:abc12    1.0 KB    24 hours ago    \n",
-		},
-		{
-			name:          "server error",
-			args:          []string{},
-			expectedError: "server error",
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			mockServer := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-				if r.URL.Path != "/api/tags" || r.Method != http.MethodGet {
-					t.Errorf("unexpected request to %s %s", r.Method, r.URL.Path)
-					http.Error(w, "not found", http.StatusNotFound)
-					return
-				}
-
-				if tt.expectedError != "" {
-					http.Error(w, tt.expectedError, http.StatusInternalServerError)
-					return
-				}
-
-				response := api.ListResponse{Models: tt.serverResponse}
-				if err := json.NewEncoder(w).Encode(response); err != nil {
-					t.Fatal(err)
-				}
-			}))
-			defer mockServer.Close()
-
-			t.Setenv("OLLAMA_HOST", mockServer.URL)
-
-			cmd := &cobra.Command{}
-			cmd.SetContext(t.Context())
-
-			// Capture stdout
-			oldStdout := os.Stdout
-			r, w, _ := os.Pipe()
-			os.Stdout = w
-
-			err := ListHandler(cmd, tt.args)
-
-			// Restore stdout and get output
-			w.Close()
-			os.Stdout = oldStdout
-			output, _ := io.ReadAll(r)
-
-			if tt.expectedError == "" {
-				if err != nil {
-					t.Errorf("expected no error, got %v", err)
-				}
-				if got := string(output); got != tt.expectedOutput {
-					t.Errorf("expected output:\n%s\ngot:\n%s", tt.expectedOutput, got)
-				}
-			} else {
-				if err == nil || !strings.Contains(err.Error(), tt.expectedError) {
-					t.Errorf("expected error containing %q, got %v", tt.expectedError, err)
-				}
-			}
-		})
-	}
-}
-
-func TestCreateHandler(t *testing.T) {
-	tests := []struct {
-		name           string
-		modelName      string
-		modelFile      string
-		serverResponse map[string]func(w http.ResponseWriter, r *http.Request)
-		expectedError  string
-		expectedOutput string
-	}{
-		{
-			name:      "successful create",
-			modelName: "test-model",
-			modelFile: "FROM foo",
-			serverResponse: map[string]func(w http.ResponseWriter, r *http.Request){
-				"/api/create": func(w http.ResponseWriter, r *http.Request) {
-					if r.Method != http.MethodPost {
-						t.Errorf("expected POST request, got %s", r.Method)
-					}
-
-					req := api.CreateRequest{}
-					if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
-						http.Error(w, err.Error(), http.StatusBadRequest)
-						return
-					}
-
-					if req.Model != "test-model" {
-						t.Errorf("expected model name 'test-model', got %s", req.Name)
-					}
-
-					if req.From != "foo" {
-						t.Errorf("expected from 'foo', got %s", req.From)
-					}
-
-					responses := []api.ProgressResponse{
-						{Status: "using existing layer sha256:56bb8bd477a519ffa694fc449c2413c6f0e1d3b1c88fa7e3c9d88d3ae49d4dcb"},
-						{Status: "writing manifest"},
-						{Status: "success"},
-					}
-
-					for _, resp := range responses {
-						if err := json.NewEncoder(w).Encode(resp); err != nil {
-							http.Error(w, err.Error(), http.StatusInternalServerError)
-							return
-						}
-						w.(http.Flusher).Flush()
-					}
-				},
-			},
-			expectedOutput: "",
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			mockServer := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-				handler, ok := tt.serverResponse[r.URL.Path]
-				if !ok {
-					t.Errorf("unexpected request to %s", r.URL.Path)
-					http.Error(w, "not found", http.StatusNotFound)
-					return
-				}
-				handler(w, r)
-			}))
-			t.Setenv("OLLAMA_HOST", mockServer.URL)
-			t.Cleanup(mockServer.Close)
-			tempFile, err := os.CreateTemp(t.TempDir(), "modelfile")
-			if err != nil {
-				t.Fatal(err)
-			}
-			defer os.Remove(tempFile.Name())
-
-			if _, err := tempFile.WriteString(tt.modelFile); err != nil {
-				t.Fatal(err)
-			}
-			if err := tempFile.Close(); err != nil {
-				t.Fatal(err)
-			}
-
-			cmd := &cobra.Command{}
-			cmd.Flags().String("file", "", "")
-			if err := cmd.Flags().Set("file", tempFile.Name()); err != nil {
-				t.Fatal(err)
-			}
-
-			cmd.Flags().Bool("insecure", false, "")
-			cmd.SetContext(t.Context())
-
-			// Redirect stderr to capture progress output
-			oldStderr := os.Stderr
-			r, w, _ := os.Pipe()
-			os.Stderr = w
-
-			// Capture stdout for the "Model pushed" message
-			oldStdout := os.Stdout
-			outR, outW, _ := os.Pipe()
-			os.Stdout = outW
-
-			err = CreateHandler(cmd, []string{tt.modelName})
-
-			// Restore stderr
-			w.Close()
-			os.Stderr = oldStderr
-			// drain the pipe
-			if _, err := io.ReadAll(r); err != nil {
-				t.Fatal(err)
-			}
-
-			// Restore stdout and get output
-			outW.Close()
-			os.Stdout = oldStdout
-			stdout, _ := io.ReadAll(outR)
-
-			if tt.expectedError == "" {
-				if err != nil {
-					t.Errorf("expected no error, got %v", err)
-				}
-
-				if tt.expectedOutput != "" {
-					if got := string(stdout); got != tt.expectedOutput {
-						t.Errorf("expected output %q, got %q", tt.expectedOutput, got)
-					}
-				}
-			}
-		})
-	}
-}
-
-func TestNewCreateRequest(t *testing.T) {
-	tests := []struct {
-		name     string
-		from     string
-		opts     runOptions
-		expected *api.CreateRequest
-	}{
-		{
-			"basic test",
-			"newmodel",
-			runOptions{
-				Model:       "mymodel",
-				ParentModel: "",
-				Prompt:      "You are a fun AI agent",
-				Messages:    []api.Message{},
-				WordWrap:    true,
-			},
-			&api.CreateRequest{
-				From:  "mymodel",
-				Model: "newmodel",
-			},
-		},
-		{
-			"parent model test",
-			"newmodel",
-			runOptions{
-				Model:       "mymodel",
-				ParentModel: "parentmodel",
-				Messages:    []api.Message{},
-				WordWrap:    true,
-			},
-			&api.CreateRequest{
-				From:  "parentmodel",
-				Model: "newmodel",
-			},
-		},
-		{
-			"parent model as filepath test",
-			"newmodel",
-			runOptions{
-				Model:       "mymodel",
-				ParentModel: "/some/file/like/etc/passwd",
-				Messages:    []api.Message{},
-				WordWrap:    true,
-			},
-			&api.CreateRequest{
-				From:  "mymodel",
-				Model: "newmodel",
-			},
-		},
-		{
-			"parent model as windows filepath test",
-			"newmodel",
-			runOptions{
-				Model:       "mymodel",
-				ParentModel: "D:\\some\\file\\like\\etc\\passwd",
-				Messages:    []api.Message{},
-				WordWrap:    true,
-			},
-			&api.CreateRequest{
-				From:  "mymodel",
-				Model: "newmodel",
-			},
-		},
-		{
-			"options test",
-			"newmodel",
-			runOptions{
-				Model:       "mymodel",
-				ParentModel: "parentmodel",
-				Options: map[string]any{
-					"temperature": 1.0,
-				},
-			},
-			&api.CreateRequest{
-				From:  "parentmodel",
-				Model: "newmodel",
-				Parameters: map[string]any{
-					"temperature": 1.0,
-				},
-			},
-		},
-		{
-			"messages test",
-			"newmodel",
-			runOptions{
-				Model:       "mymodel",
-				ParentModel: "parentmodel",
-				System:      "You are a fun AI agent",
-				Messages: []api.Message{
-					{
-						Role:    "user",
-						Content: "hello there!",
-					},
-					{
-						Role:    "assistant",
-						Content: "hello to you!",
-					},
-				},
-				WordWrap: true,
-			},
-			&api.CreateRequest{
-				From:   "parentmodel",
-				Model:  "newmodel",
-				System: "You are a fun AI agent",
-				Messages: []api.Message{
-					{
-						Role:    "user",
-						Content: "hello there!",
-					},
-					{
-						Role:    "assistant",
-						Content: "hello to you!",
-					},
-				},
-			},
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			actual := NewCreateRequest(tt.from, tt.opts)
-			if !cmp.Equal(actual, tt.expected) {
-				t.Errorf("expected output %#v, got %#v", tt.expected, actual)
-			}
-		})
-	}
-}

cmd/interactive.go

@@ -13,12 +13,13 @@ import (
 	"strings"
 
 	"github.com/spf13/cobra"
+	"golang.org/x/exp/maps"
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
+	"github.com/ollama/ollama/parser"
 	"github.com/ollama/ollama/readline"
 	"github.com/ollama/ollama/types/errtypes"
-	"github.com/ollama/ollama/types/model"
 )
 
 type MultilineState int
@@ -44,7 +45,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "Use \"\"\" to begin a multi-line message.")
 
 		if opts.MultiModal {
-			fmt.Fprintf(os.Stderr, "Use %s to include .jpg, .png, or .webp images.\n", filepath.FromSlash("/path/to/file"))
+			fmt.Fprintf(os.Stderr, "Use %s to include .jpg or .png images.\n", filepath.FromSlash("/path/to/file"))
 		}
 
 		fmt.Fprintln(os.Stderr, "")
@@ -62,8 +63,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "  /set noformat          Disable formatting")
 		fmt.Fprintln(os.Stderr, "  /set verbose           Show LLM stats")
 		fmt.Fprintln(os.Stderr, "  /set quiet             Disable LLM stats")
-		fmt.Fprintln(os.Stderr, "  /set think             Enable thinking")
-		fmt.Fprintln(os.Stderr, "  /set nothink           Disable thinking")
 		fmt.Fprintln(os.Stderr, "")
 	}
 
@@ -130,7 +129,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 
 	var sb strings.Builder
 	var multiline MultilineState
-	var thinkExplicitlySet bool = opts.Think != nil
 
 	for {
 		line, err := scanner.Readline()
@@ -198,19 +196,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 			opts.Model = args[1]
 			opts.Messages = []api.Message{}
 			fmt.Printf("Loading model '%s'\n", opts.Model)
-			opts.Think, err = inferThinkingOption(nil, &opts, thinkExplicitlySet)
-			if err != nil {
-				return err
-			}
 			if err := loadOrUnloadModel(cmd, &opts); err != nil {
-				if strings.Contains(err.Error(), "not found") {
-					fmt.Printf("error: %v\n", err)
-					continue
-				}
-				if strings.Contains(err.Error(), "does not support thinking") {
-					fmt.Printf("error: %v\n", err)
-					continue
-				}
 				return err
 			}
 			continue
@@ -227,7 +213,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 				return err
 			}
 
-			req := NewCreateRequest(args[1], opts)
+			req := &api.CreateRequest{
+				Name:      args[1],
+				Modelfile: buildModelfile(opts),
+			}
 			fn := func(resp api.ProgressResponse) error { return nil }
 			err = client.Create(cmd.Context(), req, fn)
 			if err != nil {
@@ -271,35 +260,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 						return err
 					}
 					fmt.Println("Set 'quiet' mode.")
-				case "think":
-					thinkValue := api.ThinkValue{Value: true}
-					var maybeLevel string
-					if len(args) > 2 {
-						maybeLevel = args[2]
-					}
-					if maybeLevel != "" {
-						// TODO(drifkin): validate the level, could be model dependent
-						// though... It will also be validated on the server once a call is
-						// made.
-						thinkValue.Value = maybeLevel
-					}
-					opts.Think = &thinkValue
-					thinkExplicitlySet = true
-					if client, err := api.ClientFromEnvironment(); err == nil {
-						ensureThinkingSupport(cmd.Context(), client, opts.Model)
-					}
-					if maybeLevel != "" {
-						fmt.Printf("Set 'think' mode to '%s'.\n", maybeLevel)
-					} else {
-						fmt.Println("Set 'think' mode.")
-					}
-				case "nothink":
-					opts.Think = &api.ThinkValue{Value: false}
-					thinkExplicitlySet = true
-					if client, err := api.ClientFromEnvironment(); err == nil {
-						ensureThinkingSupport(cmd.Context(), client, opts.Model)
-					}
-					fmt.Println("Set 'nothink' mode.")
 				case "format":
 					if len(args) < 3 || args[2] != "json" {
 						fmt.Println("Invalid or missing format. For 'json' mode use '/set format json'")
@@ -359,6 +319,8 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 						opts.Messages = append(opts.Messages, newMessage)
 					}
 					fmt.Println("Set system message.")
+					sb.Reset()
+
 					sb.Reset()
 					continue
 				default:
@@ -388,7 +350,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 
 				switch args[1] {
 				case "info":
-					_ = showInfo(resp, false, os.Stderr)
+					_ = showInfo(resp, os.Stderr)
 				case "license":
 					if resp.License == "" {
 						fmt.Println("No license was specified for this model.")
@@ -398,21 +360,18 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 				case "modelfile":
 					fmt.Println(resp.Modelfile)
 				case "parameters":
-					fmt.Println("Model defined parameters:")
 					if resp.Parameters == "" {
-						fmt.Println("  No additional parameters were specified for this model.")
+						fmt.Println("No parameters were specified for this model.")
 					} else {
-						for _, l := range strings.Split(resp.Parameters, "\n") {
-							fmt.Printf("  %s\n", l)
+						if len(opts.Options) > 0 {
+							fmt.Println("User defined parameters:")
+							for k, v := range opts.Options {
+								fmt.Printf("%-*s %v\n", 30, k, v)
+							}
+							fmt.Println()
 						}
-					}
-					fmt.Println()
-					if len(opts.Options) > 0 {
-						fmt.Println("User defined parameters:")
-						for k, v := range opts.Options {
-							fmt.Printf("  %-*s %v\n", 30, k, v)
-						}
-						fmt.Println()
+						fmt.Println("Model defined parameters:")
+						fmt.Println(resp.Parameters)
 					}
 				case "system":
 					switch {
@@ -491,12 +450,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 
 			assistant, err := chat(cmd, opts)
 			if err != nil {
-				if strings.Contains(err.Error(), "does not support thinking") ||
-					strings.Contains(err.Error(), "invalid think value") {
-					fmt.Printf("error: %v\n", err)
-					sb.Reset()
-					continue
-				}
 				return err
 			}
 			if assistant != nil {
@@ -508,32 +461,36 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 	}
 }
 
-func NewCreateRequest(name string, opts runOptions) *api.CreateRequest {
-	parentModel := opts.ParentModel
-
-	modelName := model.ParseName(parentModel)
-	if !modelName.IsValid() {
-		parentModel = ""
-	}
-
-	req := &api.CreateRequest{
-		Model: name,
-		From:  cmp.Or(parentModel, opts.Model),
-	}
+func buildModelfile(opts runOptions) string {
+	var f parser.File
+	f.Commands = append(f.Commands, parser.Command{Name: "model", Args: cmp.Or(opts.ParentModel, opts.Model)})
 
 	if opts.System != "" {
-		req.System = opts.System
+		f.Commands = append(f.Commands, parser.Command{Name: "system", Args: opts.System})
 	}
 
-	if len(opts.Options) > 0 {
-		req.Parameters = opts.Options
+	keys := maps.Keys(opts.Options)
+	slices.Sort(keys)
+	for _, k := range keys {
+		v := opts.Options[k]
+		var cmds []parser.Command
+		switch t := v.(type) {
+		case []string:
+			for _, s := range t {
+				cmds = append(cmds, parser.Command{Name: k, Args: s})
+			}
+		default:
+			cmds = append(cmds, parser.Command{Name: k, Args: fmt.Sprintf("%v", t)})
+		}
+
+		f.Commands = append(f.Commands, cmds...)
 	}
 
-	if len(opts.Messages) > 0 {
-		req.Messages = opts.Messages
+	for _, msg := range opts.Messages {
+		f.Commands = append(f.Commands, parser.Command{Name: "message", Args: fmt.Sprintf("%s: %s", msg.Role, msg.Content)})
 	}
 
-	return req
+	return f.String()
 }
 
 func normalizeFilePath(fp string) string {
@@ -552,7 +509,6 @@ func normalizeFilePath(fp string) string {
 		"\\\\", "\\", // Escaped backslash
 		"\\*", "*", // Escaped asterisk
 		"\\?", "?", // Escaped question mark
-		"\\~", "~", // Escaped tilde
 	).Replace(fp)
 }
 
@@ -560,7 +516,7 @@ func extractFileNames(input string) []string {
 	// Regex to match file paths starting with optional drive letter, / ./ \ or .\ and include escaped or unescaped spaces (\ or %20)
 	// and followed by more characters and a file extension
 	// This will capture non filename strings, but we'll check for file existence to remove mismatches
-	regexPattern := `(?:[a-zA-Z]:)?(?:\./|/|\\)[\S\\ ]+?\.(?i:jpg|jpeg|png|webp)\b`
+	regexPattern := `(?:[a-zA-Z]:)?(?:\./|/|\\)[\S\\ ]+?\.(?i:jpg|jpeg|png|svg)\b`
 	re := regexp.MustCompile(regexPattern)
 
 	return re.FindAllString(input, -1)
@@ -580,8 +536,6 @@ func extractFileData(input string) (string, []api.ImageData, error) {
 			return "", imgs, err
 		}
 		fmt.Fprintf(os.Stderr, "Added image '%s'\n", nfp)
-		input = strings.ReplaceAll(input, "'"+nfp+"'", "")
-		input = strings.ReplaceAll(input, "'"+fp+"'", "")
 		input = strings.ReplaceAll(input, fp, "")
 		imgs = append(imgs, data)
 	}
@@ -602,7 +556,7 @@ func getImageData(filePath string) ([]byte, error) {
 	}
 
 	contentType := http.DetectContentType(buf)
-	allowedTypes := []string{"image/jpeg", "image/jpg", "image/png", "image/webp"}
+	allowedTypes := []string{"image/jpeg", "image/jpg", "image/png"}
 	if !slices.Contains(allowedTypes, contentType) {
 		return nil, fmt.Errorf("invalid image type: %s", contentType)
 	}

cmd/interactive_test.go

@@ -1,86 +1,107 @@
 package cmd
 
 import (
-	"os"
-	"path/filepath"
 	"testing"
 
+	"github.com/google/go-cmp/cmp"
 	"github.com/stretchr/testify/assert"
+
+	"github.com/ollama/ollama/api"
 )
 
 func TestExtractFilenames(t *testing.T) {
 	// Unix style paths
 	input := ` some preamble 
- ./relative\ path/one.png inbetween1 ./not a valid two.jpg inbetween2 ./1.svg
-/unescaped space /three.jpeg inbetween3 /valid\ path/dir/four.png "./quoted with spaces/five.JPG
-/unescaped space /six.webp inbetween6 /valid\ path/dir/seven.WEBP`
+ ./relative\ path/one.png inbetween1 ./not a valid two.jpg inbetween2
+/unescaped space /three.jpeg inbetween3 /valid\ path/dir/four.png "./quoted with spaces/five.svg`
 	res := extractFileNames(input)
-	assert.Len(t, res, 7)
+	assert.Len(t, res, 5)
 	assert.Contains(t, res[0], "one.png")
 	assert.Contains(t, res[1], "two.jpg")
 	assert.Contains(t, res[2], "three.jpeg")
 	assert.Contains(t, res[3], "four.png")
-	assert.Contains(t, res[4], "five.JPG")
-	assert.Contains(t, res[5], "six.webp")
-	assert.Contains(t, res[6], "seven.WEBP")
+	assert.Contains(t, res[4], "five.svg")
 	assert.NotContains(t, res[4], '"')
-	assert.NotContains(t, res, "inbetween1")
-	assert.NotContains(t, res, "./1.svg")
+	assert.NotContains(t, res, "inbtween")
 
 	// Windows style paths
 	input = ` some preamble
  c:/users/jdoe/one.png inbetween1 c:/program files/someplace/two.jpg inbetween2 
  /absolute/nospace/three.jpeg inbetween3 /absolute/with space/four.png inbetween4
-./relative\ path/five.JPG inbetween5 "./relative with/spaces/six.png inbetween6
-d:\path with\spaces\seven.JPEG inbetween7 c:\users\jdoe\eight.png inbetween8 
- d:\program files\someplace\nine.png inbetween9 "E:\program files\someplace\ten.PNG
-c:/users/jdoe/eleven.webp inbetween11 c:/program files/someplace/twelve.WebP inbetween12
-d:\path with\spaces\thirteen.WEBP some ending
+./relative\ path/five.svg inbetween5 "./relative with/spaces/six.png inbetween6
+d:\path with\spaces\seven.svg inbetween7 c:\users\jdoe\eight.png inbetween8 
+ d:\program files\someplace\nine.png inbetween9 "E:\program files\someplace\ten.svg some ending
 `
 	res = extractFileNames(input)
-	assert.Len(t, res, 13)
-	assert.NotContains(t, res, "inbetween2")
+	assert.Len(t, res, 10)
+	assert.NotContains(t, res, "inbtween")
 	assert.Contains(t, res[0], "one.png")
 	assert.Contains(t, res[0], "c:")
 	assert.Contains(t, res[1], "two.jpg")
 	assert.Contains(t, res[1], "c:")
 	assert.Contains(t, res[2], "three.jpeg")
 	assert.Contains(t, res[3], "four.png")
-	assert.Contains(t, res[4], "five.JPG")
+	assert.Contains(t, res[4], "five.svg")
 	assert.Contains(t, res[5], "six.png")
-	assert.Contains(t, res[6], "seven.JPEG")
+	assert.Contains(t, res[6], "seven.svg")
 	assert.Contains(t, res[6], "d:")
 	assert.Contains(t, res[7], "eight.png")
 	assert.Contains(t, res[7], "c:")
 	assert.Contains(t, res[8], "nine.png")
 	assert.Contains(t, res[8], "d:")
-	assert.Contains(t, res[9], "ten.PNG")
+	assert.Contains(t, res[9], "ten.svg")
 	assert.Contains(t, res[9], "E:")
-	assert.Contains(t, res[10], "eleven.webp")
-	assert.Contains(t, res[10], "c:")
-	assert.Contains(t, res[11], "twelve.WebP")
-	assert.Contains(t, res[11], "c:")
-	assert.Contains(t, res[12], "thirteen.WEBP")
-	assert.Contains(t, res[12], "d:")
 }
 
-// Ensure that file paths wrapped in single quotes are removed with the quotes.
-func TestExtractFileDataRemovesQuotedFilepath(t *testing.T) {
-	dir := t.TempDir()
-	fp := filepath.Join(dir, "img.jpg")
-	data := make([]byte, 600)
-	copy(data, []byte{
-		0xff, 0xd8, 0xff, 0xe0, 0x00, 0x10, 'J', 'F', 'I', 'F',
-		0x00, 0x01, 0x01, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
-		0xff, 0xd9,
-	})
-	if err := os.WriteFile(fp, data, 0o600); err != nil {
-		t.Fatalf("failed to write test image: %v", err)
+func TestModelfileBuilder(t *testing.T) {
+	opts := runOptions{
+		Model:  "hork",
+		System: "You are part horse and part shark, but all hork. Do horklike things",
+		Messages: []api.Message{
+			{Role: "user", Content: "Hey there hork!"},
+			{Role: "assistant", Content: "Yes it is true, I am half horse, half shark."},
+		},
+		Options: map[string]any{
+			"temperature":      0.9,
+			"seed":             42,
+			"penalize_newline": false,
+			"stop":             []string{"hi", "there"},
+		},
 	}
 
-	input := "before '" + fp + "' after"
-	cleaned, imgs, err := extractFileData(input)
-	assert.NoError(t, err)
-	assert.Len(t, imgs, 1)
-	assert.Equal(t, cleaned, "before  after")
+	t.Run("model", func(t *testing.T) {
+		expect := `FROM hork
+SYSTEM You are part horse and part shark, but all hork. Do horklike things
+PARAMETER penalize_newline false
+PARAMETER seed 42
+PARAMETER stop hi
+PARAMETER stop there
+PARAMETER temperature 0.9
+MESSAGE user Hey there hork!
+MESSAGE assistant Yes it is true, I am half horse, half shark.
+`
+
+		actual := buildModelfile(opts)
+		if diff := cmp.Diff(expect, actual); diff != "" {
+			t.Errorf("mismatch (-want +got):\n%s", diff)
+		}
+	})
+
+	t.Run("parent model", func(t *testing.T) {
+		opts.ParentModel = "horseshark"
+		expect := `FROM horseshark
+SYSTEM You are part horse and part shark, but all hork. Do horklike things
+PARAMETER penalize_newline false
+PARAMETER seed 42
+PARAMETER stop hi
+PARAMETER stop there
+PARAMETER temperature 0.9
+MESSAGE user Hey there hork!
+MESSAGE assistant Yes it is true, I am half horse, half shark.
+`
+		actual := buildModelfile(opts)
+		if diff := cmp.Diff(expect, actual); diff != "" {
+			t.Errorf("mismatch (-want +got):\n%s", diff)
+		}
+	})
 }

cmd/runner/main.go

@@ -1,15 +0,0 @@
-package main
-
-import (
-	"fmt"
-	"os"
-
-	"github.com/ollama/ollama/runner"
-)
-
-func main() {
-	if err := runner.Execute(os.Args[1:]); err != nil {
-		fmt.Fprintf(os.Stderr, "error: %s\n", err)
-		os.Exit(1)
-	}
-}

cmd/start_darwin.go

@@ -5,7 +5,7 @@ import (
 	"errors"
 	"os"
 	"os/exec"
-	"regexp"
+	"strings"
 
 	"github.com/ollama/ollama/api"
 )
@@ -19,12 +19,11 @@ func startApp(ctx context.Context, client *api.Client) error {
 	if err != nil {
 		return err
 	}
-	r := regexp.MustCompile(`^.*/Ollama\s?\d*.app`)
-	m := r.FindStringSubmatch(link)
-	if len(m) != 1 {
+	if !strings.Contains(link, "Ollama.app") {
 		return errors.New("could not find ollama app")
 	}
-	if err := exec.Command("/usr/bin/open", "-j", "-a", m[0], "--args", "--fast-startup").Run(); err != nil {
+	path := strings.Split(link, "Ollama.app")
+	if err := exec.Command("/usr/bin/open", "-a", path[0]+"Ollama.app").Run(); err != nil {
 		return err
 	}
 	return waitForServer(ctx, client)

cmd/start_windows.go

@@ -4,27 +4,17 @@ import (
 	"context"
 	"errors"
 	"fmt"
-	"log/slog"
 	"os"
 	"os/exec"
-	"path"
 	"path/filepath"
 	"strings"
 	"syscall"
-	"unsafe"
 
 	"github.com/ollama/ollama/api"
-	"golang.org/x/sys/windows"
-)
-
-const (
-	Installer = "OllamaSetup.exe"
 )
 
 func startApp(ctx context.Context, client *api.Client) error {
-	if len(isProcRunning(Installer)) > 0 {
-		return fmt.Errorf("upgrade in progress...")
-	}
+	// log.Printf("XXX Attempting to find and start ollama app")
 	AppName := "ollama app.exe"
 	exe, err := os.Executable()
 	if err != nil {
@@ -45,11 +35,14 @@ func startApp(ctx context.Context, client *api.Client) error {
 			}
 		}
 	}
+	// log.Printf("XXX attempting to start app %s", appExe)
 
 	cmd_path := "c:\\Windows\\system32\\cmd.exe"
-	cmd := exec.Command(cmd_path, "/c", appExe, "--hide", "--fast-startup")
+	cmd := exec.Command(cmd_path, "/c", appExe)
+	// TODO - these hide flags aren't working - still pops up a command window for some reason
 	cmd.SysProcAttr = &syscall.SysProcAttr{CreationFlags: 0x08000000, HideWindow: true}
 
+	// TODO this didn't help either...
 	cmd.Stdin = strings.NewReader("")
 	cmd.Stdout = os.Stdout
 	cmd.Stderr = os.Stderr
@@ -63,50 +56,3 @@ func startApp(ctx context.Context, client *api.Client) error {
 	}
 	return waitForServer(ctx, client)
 }
-
-func isProcRunning(procName string) []uint32 {
-	pids := make([]uint32, 2048)
-	var ret uint32
-	if err := windows.EnumProcesses(pids, &ret); err != nil || ret == 0 {
-		slog.Debug("failed to check for running installers", "error", err)
-		return nil
-	}
-	if ret > uint32(len(pids)) {
-		pids = make([]uint32, ret+10)
-		if err := windows.EnumProcesses(pids, &ret); err != nil || ret == 0 {
-			slog.Debug("failed to check for running installers", "error", err)
-			return nil
-		}
-	}
-	if ret < uint32(len(pids)) {
-		pids = pids[:ret]
-	}
-	var matches []uint32
-	for _, pid := range pids {
-		if pid == 0 {
-			continue
-		}
-		hProcess, err := windows.OpenProcess(windows.PROCESS_QUERY_INFORMATION|windows.PROCESS_VM_READ, false, pid)
-		if err != nil {
-			continue
-		}
-		defer windows.CloseHandle(hProcess)
-		var module windows.Handle
-		var cbNeeded uint32
-		cb := (uint32)(unsafe.Sizeof(module))
-		if err := windows.EnumProcessModules(hProcess, &module, cb, &cbNeeded); err != nil {
-			continue
-		}
-		var sz uint32 = 1024 * 8
-		moduleName := make([]uint16, sz)
-		cb = uint32(len(moduleName)) * (uint32)(unsafe.Sizeof(uint16(0)))
-		if err := windows.GetModuleBaseName(hProcess, module, &moduleName[0], cb); err != nil && err != syscall.ERROR_INSUFFICIENT_BUFFER {
-			continue
-		}
-		exeFile := path.Base(strings.ToLower(syscall.UTF16ToString(moduleName)))
-		if strings.EqualFold(exeFile, procName) {
-			matches = append(matches, pid)
-		}
-	}
-	return matches
-}

cmd/warn_thinking_test.go

@@ -1,63 +0,0 @@
-package cmd
-
-import (
-	"encoding/json"
-	"io"
-	"net/http"
-	"net/http/httptest"
-	"os"
-	"strings"
-	"testing"
-
-	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/types/model"
-)
-
-// Test that a warning is printed when thinking is requested but not supported.
-func TestWarnMissingThinking(t *testing.T) {
-	cases := []struct {
-		capabilities []model.Capability
-		expectWarn   bool
-	}{
-		{capabilities: []model.Capability{model.CapabilityThinking}, expectWarn: false},
-		{capabilities: []model.Capability{}, expectWarn: true},
-	}
-
-	for _, tc := range cases {
-		srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-			if r.URL.Path != "/api/show" || r.Method != http.MethodPost {
-				t.Fatalf("unexpected request to %s %s", r.URL.Path, r.Method)
-			}
-			var req api.ShowRequest
-			if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
-				t.Fatalf("decode request: %v", err)
-			}
-			resp := api.ShowResponse{Capabilities: tc.capabilities}
-			if err := json.NewEncoder(w).Encode(resp); err != nil {
-				t.Fatalf("encode response: %v", err)
-			}
-		}))
-		defer srv.Close()
-
-		t.Setenv("OLLAMA_HOST", srv.URL)
-		client, err := api.ClientFromEnvironment()
-		if err != nil {
-			t.Fatal(err)
-		}
-		oldStderr := os.Stderr
-		r, w, _ := os.Pipe()
-		os.Stderr = w
-		ensureThinkingSupport(t.Context(), client, "m")
-		w.Close()
-		os.Stderr = oldStderr
-		out, _ := io.ReadAll(r)
-
-		warned := strings.Contains(string(out), "warning:")
-		if tc.expectWarn && !warned {
-			t.Errorf("expected warning, got none")
-		}
-		if !tc.expectWarn && warned {
-			t.Errorf("did not expect warning, got: %s", string(out))
-		}
-	}
-}

convert/convert.go

@@ -1,26 +1,20 @@
 package convert
 
 import (
-	"cmp"
 	"encoding/json"
 	"errors"
 	"fmt"
+	"io"
 	"io/fs"
 	"log/slog"
-	"os"
-	"slices"
 	"strings"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type ModelParameters struct {
 	Architectures []string `json:"architectures"`
 	VocabSize     uint32   `json:"vocab_size"`
-
-	TextModel struct {
-		VocabSize uint32 `json:"vocab_size"`
-	} `json:"text_config"`
 }
 
 type AdapterParameters struct {
@@ -33,8 +27,8 @@ type AdapterParameters struct {
 	} `json:"lora_parameters"`
 }
 
-func (ModelParameters) KV(t *Tokenizer) ggml.KV {
-	kv := ggml.KV{
+func (ModelParameters) KV(t *Tokenizer) fileutils.KV {
+	kv := fileutils.KV{
 		"general.file_type":            uint32(1),
 		"general.quantization_version": uint32(2),
 		"tokenizer.ggml.pre":           t.Pre,
@@ -53,17 +47,14 @@ func (ModelParameters) KV(t *Tokenizer) ggml.KV {
 	}
 
 	for _, sv := range t.SpecialVocabulary {
-		kv[fmt.Sprintf("tokenizer.ggml.add_%s_token", sv.Key())] = sv.AddToken
 		kv[fmt.Sprintf("tokenizer.ggml.%s_token_id", sv.Key())] = uint32(sv.ID)
-		if len(sv.IDs) > 0 {
-			kv[fmt.Sprintf("tokenizer.ggml.%s_token_ids", sv.Key())] = sv.IDs
-		}
+		kv[fmt.Sprintf("tokenizer.ggml.add_%s_token", sv.Key())] = sv.AddToken
 	}
 
 	return kv
 }
 
-func (p AdapterParameters) KV() ggml.KV {
+func (p AdapterParameters) KV() fileutils.KV {
 	var alpha float32
 	if p.LoraParameters.Alpha == 0 {
 		alpha = float32(p.Alpha)
@@ -71,7 +62,7 @@ func (p AdapterParameters) KV() ggml.KV {
 		alpha = p.LoraParameters.Alpha
 	}
 
-	kv := ggml.KV{
+	kv := fileutils.KV{
 		"adapter.lora.alpha": alpha,
 		"adapter.type":       "lora",
 		"general.file_type":  uint32(1),
@@ -88,17 +79,27 @@ func (ModelParameters) specialTokenTypes() []string {
 	}
 }
 
+func (ModelParameters) writeFile(ws io.WriteSeeker, kv fileutils.KV, ts []fileutils.Tensor) error {
+	return fileutils.WriteGGUF(ws, kv, ts)
+}
+
+func (AdapterParameters) writeFile(ws io.WriteSeeker, kv fileutils.KV, ts []fileutils.Tensor) error {
+	return fileutils.WriteGGUF(ws, kv, ts)
+}
+
 type ModelConverter interface {
 	// KV maps parameters to LLM key-values
-	KV(*Tokenizer) ggml.KV
+	KV(*Tokenizer) fileutils.KV
 	// Tensors maps input tensors to LLM tensors. Model specific modifications can be done here.
-	Tensors([]Tensor) []*ggml.Tensor
+	Tensors([]Tensor) []fileutils.Tensor
 	// Replacements returns a list of string pairs to replace in tensor names.
 	// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
 	Replacements() []string
 
 	// specialTokenTypes returns any special token types the model uses
 	specialTokenTypes() []string
+	// writeFile writes the model to the provided io.WriteSeeker
+	writeFile(io.WriteSeeker, fileutils.KV, []fileutils.Tensor) error
 }
 
 type moreParser interface {
@@ -107,15 +108,17 @@ type moreParser interface {
 
 type AdapterConverter interface {
 	// KV maps parameters to LLM key-values
-	KV(ggml.KV) ggml.KV
+	KV(fileutils.KV) fileutils.KV
 	// Tensors maps input tensors to LLM tensors. Adapter specific modifications can be done here.
-	Tensors([]Tensor) []*ggml.Tensor
+	Tensors([]Tensor) []fileutils.Tensor
 	// Replacements returns a list of string pairs to replace in tensor names.
 	// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
 	Replacements() []string
+
+	writeFile(io.WriteSeeker, fileutils.KV, []fileutils.Tensor) error
 }
 
-func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ggml.KV) error {
+func ConvertAdapter(fsys fs.FS, ws io.WriteSeeker, baseKV fileutils.KV) error {
 	bts, err := fs.ReadFile(fsys, "adapter_config.json")
 	if err != nil {
 		return err
@@ -150,14 +153,14 @@ func ConvertAdapter(fsys fs.FS, f *os.File, baseKV ggml.KV) error {
 		return err
 	}
 
-	return writeFile(f, conv.KV(baseKV), conv.Tensors(ts))
+	return conv.writeFile(ws, conv.KV(baseKV), conv.Tensors(ts))
 }
 
 // Convert writes an Ollama compatible model to the provided io.WriteSeeker based on configurations
 // and files it finds in the input path.
 // Supported input model formats include safetensors.
 // Supported input tokenizers files include tokenizer.json (preferred) and tokenizer.model.
-func ConvertModel(fsys fs.FS, f *os.File) error {
+func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 	bts, err := fs.ReadFile(fsys, "config.json")
 	if err != nil {
 		return err
@@ -174,38 +177,20 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 
 	var conv ModelConverter
 	switch p.Architectures[0] {
-	case "LlamaForCausalLM":
+	case "LlamaForCausalLM", "MistralForCausalLM":
 		conv = &llamaModel{}
-	case "MllamaForConditionalGeneration":
-		conv = &mllamaModel{}
-	case "Llama4ForConditionalGeneration":
-		conv = &llama4Model{}
-	case "Mistral3ForConditionalGeneration":
-		conv = &mistral3Model{}
 	case "MixtralForCausalLM":
 		conv = &mixtralModel{}
 	case "GemmaForCausalLM":
 		conv = &gemmaModel{}
 	case "Gemma2ForCausalLM":
 		conv = &gemma2Model{}
-	case "Gemma3ForCausalLM", "Gemma3ForConditionalGeneration":
-		conv = &gemma3Model{Architecture: p.Architectures[0]}
-	case "Gemma3nForConditionalGeneration":
-		conv = &gemma3nModel{}
 	case "Phi3ForCausalLM":
 		conv = &phi3Model{}
-	case "Qwen2ForCausalLM":
-		conv = &qwen2Model{}
-	case "Qwen2_5_VLForConditionalGeneration":
-		conv = &qwen25VLModel{}
 	case "BertModel":
 		conv = &bertModel{}
-	case "CohereForCausalLM":
-		conv = &commandrModel{}
-	case "GptOssForCausalLM":
-		conv = &gptossModel{}
 	default:
-		return fmt.Errorf("unsupported architecture %q", p.Architectures[0])
+		return errors.New("unsupported architecture")
 	}
 
 	if err := json.Unmarshal(bts, conv); err != nil {
@@ -223,22 +208,17 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 		return err
 	}
 
-	vocabSize := int(cmp.Or(p.VocabSize, p.TextModel.VocabSize))
-
+	vocabSize := int(p.VocabSize)
 	switch {
-	case vocabSize == 0:
-		slog.Debug("vocabulary size was not explicitly set by the model", "default size", len(t.Vocabulary.Tokens))
 	case vocabSize > len(t.Vocabulary.Tokens):
-		slog.Debug("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
+		slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
 		for i := range vocabSize - len(t.Vocabulary.Tokens) {
 			t.Vocabulary.Tokens = append(t.Vocabulary.Tokens, fmt.Sprintf("[PAD%d]", i))
 			t.Vocabulary.Scores = append(t.Vocabulary.Scores, -1)
 			t.Vocabulary.Types = append(t.Vocabulary.Types, tokenTypeUserDefined)
 		}
 	case vocabSize < len(t.Vocabulary.Tokens):
-		slog.Debug("vocabulary is larger than expected", "want", vocabSize, "got", len(t.Vocabulary.Tokens))
-		p.VocabSize = uint32(len(t.Vocabulary.Tokens))
-		p.TextModel.VocabSize = uint32(len(t.Vocabulary.Tokens))
+		return fmt.Errorf("vocabulary is larger than expected '%d' instead of '%d'", len(t.Vocabulary.Tokens), vocabSize)
 	default:
 		slog.Debug("vocabulary", "size", len(t.Vocabulary.Tokens))
 	}
@@ -248,13 +228,5 @@ func ConvertModel(fsys fs.FS, f *os.File) error {
 		return err
 	}
 
-	return writeFile(f, conv.KV(t), conv.Tensors(ts))
-}
-
-func writeFile(f *os.File, kv ggml.KV, ts []*ggml.Tensor) error {
-	for i := range ts {
-		ts[i].Shape = slices.Clone(ts[i].Shape)
-		slices.Reverse(ts[i].Shape)
-	}
-	return ggml.WriteGGUF(f, kv, ts)
+	return conv.writeFile(ws, conv.KV(t), conv.Tensors(ts))
 }

convert/convert_bert.go

@@ -8,7 +8,7 @@ import (
 	"slices"
 	"strings"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type bertModel struct {
@@ -28,7 +28,6 @@ type bertModel struct {
 	LayerNormEPS          float32 `json:"layer_norm_eps"`
 	LayerNormEpsilon      float32 `json:"layer_norm_epsilon"`
 	NormEpsilon           float32 `json:"norm_epsilon"`
-	normalizeEmbeddings   bool
 
 	PoolingType uint32
 }
@@ -55,11 +54,9 @@ func (p *bertModel) parseMore(fsys fs.FS) error {
 
 	var pooling string
 	for _, m := range modules {
-		switch m.Type {
-		case "sentence_transformers.models.Pooling":
+		if m.Type == "sentence_transformers.models.Pooling" {
 			pooling = m.Path
-		case "sentence_transformers.models.Normalize":
-			p.normalizeEmbeddings = true
+			break
 		}
 	}
 
@@ -88,12 +85,11 @@ func (p *bertModel) parseMore(fsys fs.FS) error {
 	return nil
 }
 
-func (p *bertModel) KV(t *Tokenizer) ggml.KV {
+func (p *bertModel) KV(t *Tokenizer) fileutils.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "bert"
 	kv["bert.attention.causal"] = false
 	kv["bert.pooling_type"] = p.PoolingType
-	kv["bert.normalize_embeddings"] = p.normalizeEmbeddings
 
 	kv["bert.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer)
 
@@ -136,8 +132,8 @@ func (p *bertModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p *bertModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *bertModel) Tensors(ts []Tensor) []fileutils.Tensor {
+	var out []fileutils.Tensor
 	for _, t := range ts {
 		if slices.Contains([]string{
 			"embeddings.position_ids",
@@ -147,7 +143,7 @@ func (p *bertModel) Tensors(ts []Tensor) []*ggml.Tensor {
 			continue
 		}
 
-		out = append(out, &ggml.Tensor{
+		out = append(out, fileutils.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),

convert/convert_commandr.go

@@ -1,76 +0,0 @@
-package convert
-
-import (
-	"cmp"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type commandrModel struct {
-	ModelParameters
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	HiddenLayers          uint32  `json:"num_hidden_layers"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	NumAttentionHeads     uint32  `json:"num_attention_heads"`
-	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-	LayerNormEPS          float32 `json:"layer_norm_eps"`
-	RopeTheta             float32 `json:"rope_theta"`
-	UseQKNorm             bool    `json:"use_qk_norm"`
-	MaxLength             uint32  `json:"model_max_length"`
-	LogitScale            float32 `json:"logit_scale"`
-	NCtx                  uint32  `json:"n_ctx"`
-}
-
-var _ ModelConverter = (*commandrModel)(nil)
-
-func (p *commandrModel) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "command-r"
-	kv["general.name"] = "command-r"
-	kv["command-r.context_length"] = cmp.Or(p.MaxLength, p.MaxPositionEmbeddings, p.NCtx)
-	kv["command-r.embedding_length"] = p.HiddenSize
-	kv["command-r.block_count"] = p.HiddenLayers
-	kv["command-r.feed_forward_length"] = p.IntermediateSize
-	kv["command-r.attention.head_count"] = p.NumAttentionHeads
-	kv["command-r.attention.head_count_kv"] = p.NumKeyValueHeads
-	kv["command-r.attention.layer_norm_epsilon"] = p.LayerNormEPS
-	kv["command-r.rope.freq_base"] = p.RopeTheta
-	kv["command-r.max_position_embeddings"] = cmp.Or(p.MaxLength, p.MaxPositionEmbeddings)
-	kv["command-r.logit_scale"] = p.LogitScale
-	kv["command-r.rope.scaling.type"] = "none"
-
-	return kv
-}
-
-func (p *commandrModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-	for _, t := range ts {
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *commandrModel) Replacements() []string {
-	return []string{
-		"self_attn.q_norm", "attn_q_norm",
-		"self_attn.k_norm", "attn_k_norm",
-		"model.layers", "blk",
-		"input_layernorm", "attn_norm",
-		"mlp.down_proj", "ffn_down",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.up_proj", "ffn_up",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.o_proj", "attn_output",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.v_proj", "attn_v",
-		"model.norm", "output_norm",
-		"model.embed_tokens", "token_embd",
-	}
-}

convert/convert_gemma.go

@@ -6,7 +6,7 @@ import (
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type gemmaModel struct {
@@ -23,7 +23,7 @@ type gemmaModel struct {
 
 var _ ModelConverter = (*gemmaModel)(nil)
 
-func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
+func (p *gemmaModel) KV(t *Tokenizer) fileutils.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma"
 	kv["gemma.context_length"] = p.MaxPositionEmbeddings
@@ -42,14 +42,14 @@ func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p *gemmaModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *gemmaModel) Tensors(ts []Tensor) []fileutils.Tensor {
+	var out []fileutils.Tensor
 	for _, t := range ts {
-		if !strings.HasPrefix(t.Name(), "v.") && strings.HasSuffix(t.Name(), "_norm.weight") {
+		if strings.HasSuffix(t.Name(), "_norm.weight") {
 			t.SetRepacker(p.addOne)
 		}
 
-		out = append(out, &ggml.Tensor{
+		out = append(out, fileutils.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),

convert/convert_gemma2.go

@@ -1,6 +1,8 @@
 package convert
 
-import "github.com/ollama/ollama/fs/ggml"
+import (
+	"github.com/ollama/ollama/fileutils"
+)
 
 type gemma2Model struct {
 	gemmaModel
@@ -9,7 +11,7 @@ type gemma2Model struct {
 	FinalLogitSoftcap     float32 `json:"final_logit_softcapping"`
 }
 
-func (p *gemma2Model) KV(t *Tokenizer) ggml.KV {
+func (p *gemma2Model) KV(t *Tokenizer) fileutils.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma2"
 	kv["gemma2.context_length"] = p.MaxPositionEmbeddings

convert/convert_gemma2_adapter.go

@@ -6,7 +6,7 @@ import (
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type gemma2Adapter struct {
@@ -15,14 +15,14 @@ type gemma2Adapter struct {
 
 var _ AdapterConverter = (*gemma2Adapter)(nil)
 
-func (p *gemma2Adapter) KV(baseKV ggml.KV) ggml.KV {
+func (p *gemma2Adapter) KV(baseKV fileutils.KV) fileutils.KV {
 	kv := p.AdapterParameters.KV()
 	kv["general.architecture"] = "gemma2"
 	return kv
 }
 
-func (p *gemma2Adapter) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *gemma2Adapter) Tensors(ts []Tensor) []fileutils.Tensor {
+	var out []fileutils.Tensor
 	for _, t := range ts {
 		shape := t.Shape()
 		if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
@@ -31,7 +31,7 @@ func (p *gemma2Adapter) Tensors(ts []Tensor) []*ggml.Tensor {
 			t.SetRepacker(p.repack)
 		}
 
-		out = append(out, &ggml.Tensor{
+		out = append(out, fileutils.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),

convert/convert_gemma3.go

@@ -1,142 +0,0 @@
-package convert
-
-import (
-	"cmp"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type gemma3Model struct {
-	gemmaModel
-	Architecture string
-	TextModel    struct {
-		HeadDim          uint32 `json:"head_dim"`
-		HiddenSize       uint32 `json:"hidden_size"`
-		HiddenLayers     uint32 `json:"num_hidden_layers"`
-		IntermediateSize uint32 `json:"intermediate_size"`
-		SlidingWindow    uint32 `json:"sliding_window"`
-	} `json:"text_config"`
-	VisionModel struct {
-		NumAttentionHeads uint32  `json:"num_attention_heads"` // attention.head_count 16
-		LayerNormEpsilon  float32 `json:"layer_norm_eps"`      // attention.layer_norm_epsilon 1e-05
-		NumHiddenLayers   uint32  `json:"num_hidden_layers"`   // block_count 32
-		HiddenSize        uint32  `json:"hidden_size"`         // embedding_length 1280
-		IntermediateSize  uint32  `json:"intermediate_size"`   // feed_forward_length 5120
-		ImageSize         uint32  `json:"image_size"`          // image_size 560
-		NumChannels       uint32  `json:"num_channels"`        // num_channels 3
-		PatchSize         uint32  `json:"patch_size"`          // patch_size 14
-	} `json:"vision_config"`
-	MaxPositionEmbeddings    uint32  `json:"max_position_embeddings"`
-	NumAttentionHeads        uint32  `json:"num_attention_heads"`
-	NumKeyValueHeads         uint32  `json:"num_key_value_heads"`
-	RMSNormEPS               float32 `json:"rms_norm_eps"`
-	HeadDim                  uint32  `json:"head_dim"`
-	FinalLogitSoftcap        float32 `json:"final_logit_softcapping"`
-	RopeLocalTheta           float32 `json:"rope_local_base_freq"`
-	RopeGlobalTheta          float32 `json:"rope_global_base_freq"`
-	SlidingWindow            uint32  `json:"sliding_window"`
-	MultiModalTokensPerImage uint32  `json:"mm_tokens_per_image"`
-}
-
-const (
-	gemma4BLayerCount  = 34
-	gemma12BLayerCount = 48
-	gemma27BLayerCount = 62
-)
-
-func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "gemma3"
-
-	numBlocks := cmp.Or(p.HiddenLayers, p.TextModel.HiddenLayers)
-	kv["gemma3.block_count"] = numBlocks
-
-	var (
-		numHeads   uint32
-		numKVHeads uint32
-	)
-
-	switch numBlocks {
-	case gemma4BLayerCount:
-		numHeads = 8
-		numKVHeads = 4
-	case gemma12BLayerCount:
-		numHeads = 16
-		numKVHeads = 8
-	case gemma27BLayerCount:
-		numHeads = 32
-		numKVHeads = 16
-	default:
-		numHeads = p.NumAttentionHeads
-		numKVHeads = p.NumKeyValueHeads
-	}
-
-	kv["gemma3.attention.head_count"] = numHeads
-	kv["gemma3.attention.head_count_kv"] = numKVHeads
-
-	switch p.Architecture {
-	case "Gemma3ForCausalLM":
-		kv["gemma3.context_length"] = p.MaxPositionEmbeddings
-		kv["gemma3.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
-		kv["gemma3.attention.key_length"] = p.HeadDim
-		kv["gemma3.attention.value_length"] = p.HeadDim
-		kv["gemma3.attention.sliding_window"] = p.SlidingWindow
-		kv["gemma3.final_logit_softcapping"] = cmp.Or(p.FinalLogitSoftcap, 30)
-		kv["gemma3.rope.local.freq_base"] = cmp.Or(p.RopeLocalTheta, 10000.0)
-		kv["gemma3.rope.global.freq_base"] = cmp.Or(p.RopeGlobalTheta, 1000000.0)
-		kv["gemma3.embedding_length"] = p.HiddenSize
-		kv["gemma3.feed_forward_length"] = p.IntermediateSize
-	default:
-		kv["gemma3.context_length"] = cmp.Or(p.MaxPositionEmbeddings, 131072)
-		kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
-		kv["gemma3.feed_forward_length"] = p.TextModel.IntermediateSize
-		kv["gemma3.attention.sliding_window"] = p.TextModel.SlidingWindow
-		kv["gemma3.vision.block_count"] = p.VisionModel.NumHiddenLayers
-		kv["gemma3.vision.embedding_length"] = p.VisionModel.HiddenSize
-		kv["gemma3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
-		kv["gemma3.vision.image_size"] = p.VisionModel.ImageSize
-		kv["gemma3.vision.patch_size"] = p.VisionModel.PatchSize
-		kv["gemma3.vision.num_channels"] = cmp.Or(p.VisionModel.NumChannels, 3)
-		kv["gemma3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
-		kv["gemma3.vision.attention.layer_norm_epsilon"] = cmp.Or(p.VisionModel.LayerNormEpsilon, 1e-6)
-		kv["gemma3.attention.key_length"] = cmp.Or(p.TextModel.HeadDim, 256)
-		kv["gemma3.attention.value_length"] = cmp.Or(p.TextModel.HeadDim, 256)
-	}
-
-	if p.MultiModalTokensPerImage > 0 {
-		kv["gemma3.mm.tokens_per_image"] = p.MultiModalTokensPerImage
-	}
-
-	return kv
-}
-
-func (p *gemma3Model) Replacements() []string {
-	return []string{
-		"lm_head", "output",
-		"model.embed_tokens", "token_embd",
-		"model.norm", "output_norm",
-		"vision_tower.vision_model.embeddings", "v",
-		"vision_tower.vision_model", "v",
-		"vision_model.vision_model.embeddings", "v",
-		"vision_model.vision_model", "v",
-		"language_model.", "",
-		"model.layers", "blk",
-		"encoder.layers", "blk",
-		"input_layernorm", "attn_norm",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.q_norm", "attn_q_norm",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.k_norm", "attn_k_norm",
-		"self_attn.v_proj", "attn_v",
-		"self_attn.o_proj", "attn_output",
-		"self_attn.out_proj", "attn_output",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.down_proj", "ffn_down",
-		"mlp.up_proj", "ffn_up",
-		"post_attention_layernorm", "post_attention_norm",
-		"pre_feedforward_layernorm", "ffn_norm",
-		"post_feedforward_layernorm", "post_ffw_norm",
-		"input_projection_weight", "input_projection.weight",
-		"multi_modal_projector", "mm",
-	}
-}

convert/convert_gemma3n.go

@@ -1,165 +0,0 @@
-package convert
-
-import (
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-	"gonum.org/v1/gonum/stat/distuv"
-)
-
-type gemma3nModel struct {
-	ModelParameters
-
-	TextModel struct {
-		ActivationSparsityPattern []float32 `json:"activation_sparsity_pattern"`
-		AltupActiveIdx            uint32    `json:"altup_active_idx"`
-		AltupCoefClip             float32   `json:"altup_coef_clip"`
-		AltupCorrectScale         bool      `json:"altup_correct_scale"`
-		AltupLRMultiplier         float32   `json:"altup_lr_multiplier"`
-		AltupNumInputs            uint32    `json:"altup_num_inputs"`
-		HeadDim                   uint32    `json:"head_dim"`
-		HiddenSize                uint32    `json:"hidden_size"`
-		HiddenSizePerLayerInput   uint32    `json:"hidden_size_per_layer_input"`
-		IntermediateSize          uint32    `json:"intermediate_size"`
-		MaxPositionEmbeddings     uint32    `json:"max_position_embeddings"`
-		NumAttentionHeads         uint32    `json:"num_attention_heads"`
-		NumHiddenLayers           uint32    `json:"num_hidden_layers"`
-		NumKeyValueHeads          uint32    `json:"num_key_value_heads"`
-		NumKVSharedLayers         uint32    `json:"num_kv_shared_layers"`
-		RMSNormEPS                float32   `json:"rms_norm_eps"`
-		RopeLocalBaseFreq         float32   `json:"rope_local_base_freq"`
-		RopeTheta                 float32   `json:"rope_theta"`
-		SlidingWindow             uint32    `json:"sliding_window"`
-		LayerTypes                []string  `json:"layer_types"`
-	} `json:"text_config"`
-	VisionModel struct{} `json:"vision_config"`
-}
-
-func (m *gemma3nModel) KV(t *Tokenizer) ggml.KV {
-	kv := m.ModelParameters.KV(t)
-	kv["general.architecture"] = "gemma3n"
-	kv["gemma3n.activation_sparsity_scale"] = slices.Collect(func(yield func(float32) bool) {
-		norm := distuv.Normal{Mu: 0, Sigma: 1}
-		for _, v := range m.TextModel.ActivationSparsityPattern {
-			if !yield(float32(norm.Quantile(float64(v)))) {
-				break
-			}
-		}
-	})
-	kv["gemma3n.altup.active_idx"] = m.TextModel.AltupActiveIdx
-	kv["gemma3n.altup.correct_scale"] = m.TextModel.AltupCorrectScale
-	kv["gemma3n.altup.lr_multiplier"] = m.TextModel.AltupLRMultiplier
-	kv["gemma3n.altup.num_inputs"] = m.TextModel.AltupNumInputs
-	kv["gemma3n.attention.head_count_kv"] = m.TextModel.NumKeyValueHeads
-	kv["gemma3n.attention.head_count"] = m.TextModel.NumAttentionHeads
-	kv["gemma3n.attention.layer_norm_rms_epsilon"] = m.TextModel.RMSNormEPS
-	kv["gemma3n.attention.sliding_window"] = m.TextModel.SlidingWindow
-	kv["gemma3n.attention.sliding_window_pattern"] = slices.Collect(func(yield func(bool) bool) {
-		for _, t := range m.TextModel.LayerTypes {
-			if !yield(t == "sliding_attention") {
-				break
-			}
-		}
-	})
-	kv["gemma3n.attention.shared_kv_layers"] = m.TextModel.NumKVSharedLayers
-	kv["gemma3n.block_count"] = m.TextModel.NumHiddenLayers
-	kv["gemma3n.context_length"] = m.TextModel.MaxPositionEmbeddings
-	kv["gemma3n.embedding_length_per_layer_input"] = m.TextModel.HiddenSizePerLayerInput
-	kv["gemma3n.embedding_length"] = m.TextModel.HiddenSize
-	kv["gemma3n.feed_forward_length"] = m.TextModel.IntermediateSize
-	kv["gemma3n.head_dim"] = m.TextModel.HeadDim
-	kv["gemma3n.rope.freq_base_local"] = m.TextModel.RopeLocalBaseFreq
-	kv["gemma3n.rope.freq_base"] = m.TextModel.RopeTheta
-	return kv
-}
-
-func (m *gemma3nModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	out, ts := mergeTensors(ts,
-		merge{"altup_proj.*.weight", "altup_proj.weight"},
-		merge{"altup_unembd_proj.*.weight", "altup_unembd_proj.weight"},
-	)
-
-	for _, t := range ts {
-		switch {
-		case strings.Contains(t.Name(), "audio_tower"),
-			strings.Contains(t.Name(), "embed_audio"),
-			strings.Contains(t.Name(), "vision_tower"),
-			strings.Contains(t.Name(), "embed_vision"):
-			// TODO: handle audio and vision towers
-			continue
-		case strings.Contains(t.Name(), "altup_predict_coef"),
-			strings.Contains(t.Name(), "altup_correct_coef"):
-			if m.TextModel.AltupCoefClip > 0 {
-				t.SetRepacker(func(name string, data []float32, shape []uint64) (_ []float32, err error) {
-					dims := make([]int, len(shape))
-					for i := range shape {
-						dims[i] = int(shape[i])
-					}
-
-					var t tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-
-					t, err = tensor.Clamp(t, -m.TextModel.AltupCoefClip, m.TextModel.AltupCoefClip)
-					if err != nil {
-						return nil, err
-					}
-
-					if err := t.Reshape(t.Shape().TotalSize()); err != nil {
-						return nil, err
-					}
-
-					return native.VectorF32(t.(*tensor.Dense))
-				})
-			}
-		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (m *gemma3nModel) Replacements() []string {
-	return []string{
-		"model.language_model.embed_tokens_per_layer", "per_layer_token_embd",
-		"model.language_model.embed_tokens", "token_embd",
-		"model.language_model.per_layer_model_projection", "per_layer_model_proj",
-		"model.language_model.per_layer_projection_norm", "per_layer_proj_norm", "model.language_model.altup_projections", "altup_proj",
-		"model.language_model.altup_unembed_projections", "altup_unembd_proj",
-		"model.language_model.norm", "output_norm",
-		"model.language_model.layers", "blk",
-
-		"input_layernorm", "attn_norm",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.q_norm", "attn_q_norm",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.k_norm", "attn_k_norm",
-		"self_attn.v_proj", "attn_v",
-		"self_attn.o_proj", "attn_output",
-		"post_attention_layernorm", "post_attention_norm",
-		"pre_feedforward_layernorm", "ffn_norm",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.up_proj", "ffn_up",
-		"mlp.down_proj", "ffn_down",
-		"post_feedforward_layernorm", "post_ffw_norm",
-		"per_layer_input_gate", "inp_gate",
-		"per_layer_projection", "proj",
-		"post_per_layer_input_norm", "post_norm",
-		"altup.", "altup_",
-		"modality_router", "router",
-		"prediction_coefs", "predict_coef",
-		"correction_coefs", "correct_coef",
-		"correct_output_scale", "correct_scale.weight",
-		"laurel.", "laurel_",
-		"linear_left", "l",
-		"linear_right", "r",
-		"post_laurel_norm", "post_norm",
-	}
-}

convert/convert_gptoss.go

@@ -1,223 +0,0 @@
-package convert
-
-import (
-	"bytes"
-	"cmp"
-	"encoding/binary"
-	"io"
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-)
-
-type gptossModel struct {
-	ModelParameters
-	HiddenLayers          uint32  `json:"num_hidden_layers"`
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	AttentionHeads        uint32  `json:"num_attention_heads"`
-	KeyValueHeads         uint32  `json:"num_key_value_heads"`
-	HeadDim               uint32  `json:"head_dim"`
-	Experts               uint32  `json:"num_experts"`
-	LocalExperts          uint32  `json:"num_local_experts"`
-	ExpertsPerToken       uint32  `json:"experts_per_token"`
-	RMSNormEpsilon        float32 `json:"rms_norm_eps"`
-	InitialContextLength  uint32  `json:"initial_context_length"`
-	RopeTheta             float32 `json:"rope_theta"`
-	RopeScalingFactor     float32 `json:"rope_scaling_factor"`
-	RopeScaling           struct {
-		Factor float32 `json:"factor"`
-	} `json:"rope_scaling"`
-	SlidingWindow uint32 `json:"sliding_window"`
-}
-
-var _ ModelConverter = (*gptossModel)(nil)
-
-func (m *gptossModel) KV(t *Tokenizer) ggml.KV {
-	kv := m.ModelParameters.KV(t)
-	kv["general.architecture"] = "gptoss"
-	kv["general.file_type"] = uint32(4)
-	kv["gptoss.context_length"] = cmp.Or(m.MaxPositionEmbeddings, uint32(m.RopeScalingFactor*float32(m.InitialContextLength)))
-	kv["gptoss.block_count"] = m.HiddenLayers
-	kv["gptoss.embedding_length"] = m.HiddenSize
-	kv["gptoss.feed_forward_length"] = m.IntermediateSize
-	kv["gptoss.expert_count"] = cmp.Or(m.Experts, m.LocalExperts)
-	kv["gptoss.expert_used_count"] = m.ExpertsPerToken
-	kv["gptoss.attention.head_count"] = m.AttentionHeads
-	kv["gptoss.attention.head_count_kv"] = m.KeyValueHeads
-	kv["gptoss.attention.key_length"] = m.HeadDim
-	kv["gptoss.attention.value_length"] = m.HeadDim
-	kv["gptoss.attention.layer_norm_rms_epsilon"] = cmp.Or(m.RMSNormEpsilon, 1e-5)
-	kv["gptoss.attention.sliding_window"] = m.SlidingWindow
-	kv["gptoss.rope.freq_base"] = m.RopeTheta
-	kv["gptoss.rope.scaling.factor"] = cmp.Or(m.RopeScalingFactor, m.RopeScaling.Factor)
-	kv["gptoss.rope.scaling.original_context_length"] = m.InitialContextLength
-	kv["tokenizer.ggml.bos_token_id"] = uint32(199998) // <|startoftext|>
-	kv["tokenizer.ggml.add_bos_token"] = false
-	kv["tokenizer.ggml.eos_token_id"] = uint32(199999) // <|endoftext|>
-	kv["tokenizer.ggml.eos_token_ids"] = []int32{
-		199999, /* <|endoftext|> */
-		200002, /* <|return|> */
-		200012, /* <|call|> */
-	}
-	kv["tokenizer.ggml.add_eos_token"] = false
-	return kv
-}
-
-func (m *gptossModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-	mxfp4s := make(map[string]*mxfp4)
-	for _, t := range ts {
-		if strings.HasSuffix(t.Name(), ".blocks") || strings.HasSuffix(t.Name(), ".scales") {
-			dot := strings.LastIndex(t.Name(), ".")
-			name, suffix := t.Name()[:dot], t.Name()[dot+1:]
-			if _, ok := mxfp4s[name]; !ok {
-				mxfp4s[name] = &mxfp4{}
-			}
-
-			switch suffix {
-			case "blocks":
-				mxfp4s[name].blocks = t
-			case "scales":
-				mxfp4s[name].scales = t
-			}
-		} else {
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    t.Shape(),
-				WriterTo: t,
-			})
-		}
-	}
-
-	for name, mxfp4 := range mxfp4s {
-		dims := mxfp4.blocks.Shape()
-
-		if !strings.HasSuffix(name, ".weight") {
-			name += ".weight"
-		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     name,
-			Kind:     uint32(ggml.TensorTypeMXFP4),
-			Shape:    []uint64{dims[0], dims[1], dims[2] * dims[3] * 2},
-			WriterTo: mxfp4,
-		})
-	}
-
-	return out
-}
-
-func (m *gptossModel) Replacements() []string {
-	var replacements []string
-	if m.MaxPositionEmbeddings > 0 {
-		// hf flavored model
-		replacements = []string{
-			"lm_head", "output",
-			"model.embed_tokens", "token_embd",
-			"model.layers", "blk",
-			"input_layernorm", "attn_norm",
-			"self_attn.q_proj", "attn_q",
-			"self_attn.k_proj", "attn_k",
-			"self_attn.v_proj", "attn_v",
-			"self_attn.o_proj", "attn_out",
-			"self_attn.sinks", "attn_sinks",
-			"post_attention_layernorm", "ffn_norm",
-			"mlp.router", "ffn_gate_inp",
-			"mlp.experts.gate_up_proj_", "ffn_gate_up_exps.",
-			"mlp.experts.down_proj_", "ffn_down_exps.",
-			"model.norm", "output_norm",
-		}
-	} else {
-		replacements = []string{
-			// noop replacements so other replacements will not be applied
-			".blocks", ".blocks",
-			".scales", ".scales",
-			// real replacements
-			"block", "blk",
-			"attn.norm", "attn_norm",
-			"attn.qkv", "attn_qkv",
-			"attn.sinks", "attn_sinks",
-			"attn.out", "attn_out",
-			"mlp.norm", "ffn_norm",
-			"mlp.gate", "ffn_gate_inp",
-			"mlp.mlp1_", "ffn_gate_up_exps.",
-			"mlp.mlp2_", "ffn_down_exps.",
-			"embedding", "token_embd",
-			"norm", "output_norm",
-			"unembedding", "output",
-			"scale", "weight",
-		}
-	}
-	return replacements
-}
-
-type mxfp4 struct {
-	blocks, scales Tensor
-}
-
-func (m *mxfp4) WriteTo(w io.Writer) (int64, error) {
-	var b bytes.Buffer
-	if _, err := m.blocks.WriteTo(&b); err != nil {
-		return 0, err
-	}
-
-	blocksDims := make([]int, len(m.blocks.Shape()))
-	for i, d := range m.blocks.Shape() {
-		blocksDims[i] = int(d)
-	}
-
-	bts := b.Bytes()
-	var tmp [16]byte
-	for i := 0; i < b.Len(); i += 16 {
-		for j := range 8 {
-			// transform a1b2c3 ... x7y8z9 -> 71xa82yb93zc
-			a, b := bts[i+j], bts[i+j+8]
-			tmp[2*j+0] = (a & 0x0F) | (b << 4)
-			tmp[2*j+1] = (a >> 4) | (b & 0xF0)
-		}
-
-		copy(bts[i:i+16], tmp[:])
-	}
-
-	var blocks tensor.Tensor = tensor.New(tensor.WithShape(blocksDims...), tensor.WithBacking(bts))
-
-	var s bytes.Buffer
-	if _, err := m.scales.WriteTo(&s); err != nil {
-		return 0, err
-	}
-
-	scalesDims := slices.Repeat([]int{1}, len(m.blocks.Shape()))
-	for i, d := range m.scales.Shape() {
-		scalesDims[i] = int(d)
-	}
-
-	var scales tensor.Tensor = tensor.New(tensor.WithShape(scalesDims...), tensor.WithBacking(s.Bytes()))
-
-	out, err := tensor.Concat(3, scales, blocks)
-	if err != nil {
-		return 0, err
-	}
-
-	out = tensor.Materialize(out)
-
-	if err := out.Reshape(out.Shape().TotalSize()); err != nil {
-		return 0, err
-	}
-
-	u8s, err := native.VectorU8(out.(*tensor.Dense))
-	if err != nil {
-		return 0, err
-	}
-
-	if err := binary.Write(w, binary.LittleEndian, u8s); err != nil {
-		return 0, err
-	}
-
-	return int64(len(u8s)), nil
-}

convert/convert_llama.go

@@ -9,7 +9,7 @@ import (
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type llamaModel struct {
@@ -28,12 +28,12 @@ type llamaModel struct {
 	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
 	RopeTheta             float32 `json:"rope_theta"`
 	RopeScaling           struct {
-		Type                          string  `json:"type"`
-		RopeType                      string  `json:"rope_type"`
-		Factor                        float32 `json:"factor"`
-		LowFrequencyFactor            float32 `json:"low_freq_factor"`
-		HighFrequencyFactor           float32 `json:"high_freq_factor"`
-		OriginalMaxPositionEmbeddings uint32  `json:"original_max_position_embeddings"`
+		Type                            string  `json:"type"`
+		RopeType                        string  `json:"rope_type"`
+		Factor                          float32 `json:"factor"`
+		LowFrequencyFactor              float32 `json:"low_freq_factor"`
+		HighFrequencyFactor             float32 `json:"high_freq_factor"`
+		OriginalMaxPositionalEmbeddings uint32  `json:"original_max_positional_embeddings"`
 
 		factors ropeFactor
 	} `json:"rope_scaling"`
@@ -42,13 +42,11 @@ type llamaModel struct {
 	LayerNormEpsilon float32 `json:"layer_norm_epsilon"`
 	NormEpsilon      float32 `json:"norm_epsilon"`
 	HeadDim          uint32  `json:"head_dim"`
-
-	skipRepack bool
 }
 
 var _ ModelConverter = (*llamaModel)(nil)
 
-func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
+func (p *llamaModel) KV(t *Tokenizer) fileutils.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "llama"
 	kv["llama.vocab_size"] = p.VocabSize
@@ -72,10 +70,6 @@ func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
 		kv["llama.rope.dimension_count"] = p.HiddenSize / headCount
 	}
 
-	if p.HeadDim > 0 {
-		kv["llama.attention.head_dim"] = p.HeadDim
-	}
-
 	if p.RopeTheta > 0 {
 		kv["llama.rope.freq_base"] = p.RopeTheta
 	}
@@ -90,7 +84,7 @@ func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
 			factorLow := cmp.Or(p.RopeScaling.LowFrequencyFactor, 1.0)
 			factorHigh := cmp.Or(p.RopeScaling.HighFrequencyFactor, 4.0)
 
-			original := cmp.Or(p.RopeScaling.OriginalMaxPositionEmbeddings, 8192)
+			original := cmp.Or(p.RopeScaling.OriginalMaxPositionalEmbeddings, 8192)
 			lambdaLow := float32(original) / factorLow
 			lambdaHigh := float32(original) / factorHigh
 
@@ -126,11 +120,11 @@ func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p *llamaModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *llamaModel) Tensors(ts []Tensor) []fileutils.Tensor {
+	var out []fileutils.Tensor
 
 	if p.RopeScaling.factors != nil {
-		out = append(out, &ggml.Tensor{
+		out = append(out, fileutils.Tensor{
 			Name:     "rope_freqs.weight",
 			Kind:     0,
 			Shape:    []uint64{uint64(len(p.RopeScaling.factors))},
@@ -139,14 +133,12 @@ func (p *llamaModel) Tensors(ts []Tensor) []*ggml.Tensor {
 	}
 
 	for _, t := range ts {
-		if strings.HasSuffix(t.Name(), "attn_q.weight") || strings.HasSuffix(t.Name(), "attn_k.weight") ||
-			strings.HasSuffix(t.Name(), "attn_q_proj.weight") || strings.HasSuffix(t.Name(), "attn_k_proj.weight") {
-			if !p.skipRepack {
-				t.SetRepacker(p.repack)
-			}
+		if strings.HasSuffix(t.Name(), "attn_q.weight") ||
+			strings.HasSuffix(t.Name(), "attn_k.weight") {
+			t.SetRepacker(p.repack)
 		}
 
-		out = append(out, &ggml.Tensor{
+		out = append(out, fileutils.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
@@ -182,9 +174,9 @@ func (p *llamaModel) repack(name string, data []float32, shape []uint64) ([]floa
 	}
 
 	var heads uint32
-	if strings.HasSuffix(name, "attn_q.weight") || strings.HasSuffix(name, "attn_q_proj.weight") {
+	if strings.HasSuffix(name, "attn_q.weight") {
 		heads = p.NumAttentionHeads
-	} else if strings.HasSuffix(name, "attn_k.weight") || strings.HasSuffix(name, "attn_k_proj.weight") {
+	} else if strings.HasSuffix(name, "attn_k.weight") {
 		heads = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
 	} else {
 		return nil, fmt.Errorf("unknown tensor for repack: %s", name)

convert/convert_llama4.go

@@ -1,169 +0,0 @@
-package convert
-
-import (
-	"slices"
-	"strings"
-
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type llama4Model struct {
-	ModelParameters
-	TextModel struct {
-		llamaModel
-		NumExpertsPerToken     uint32 `json:"num_experts_per_tok"`
-		NumLocalExperts        uint32 `json:"num_local_experts"`
-		InterleaveMOELayerStep uint32 `json:"interleave_moe_layer_step"`
-		UseQKNorm              bool   `json:"use_qk_norm"`
-		IntermediateSizeMLP    uint32 `json:"intermediate_size_mlp"`
-		AttentionChunkSize     uint32 `json:"attention_chunk_size"`
-	} `json:"text_config"`
-	VisionModel struct {
-		NumHiddenLayers   uint32  `json:"num_hidden_layers"`
-		HiddenSize        uint32  `json:"hidden_size"`
-		IntermediateSize  uint32  `json:"intermediate_size"`
-		NumAttentionHeads uint32  `json:"num_attention_heads"`
-		ImageSize         uint32  `json:"image_size"`
-		PatchSize         uint32  `json:"patch_size"`
-		RopeTheta         float32 `json:"rope_theta"`
-		NormEpsilon       float32 `json:"norm_eps"`
-		PixelShuffleRatio float32 `json:"pixel_shuffle_ratio"`
-	} `json:"vision_config"`
-}
-
-// KV implements ModelConverter.
-func (p *llama4Model) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "llama4"
-
-	for k, v := range p.TextModel.KV(t) {
-		if strings.HasPrefix(k, "llama.") {
-			kv[strings.ReplaceAll(k, "llama.", "llama4.")] = v
-		}
-	}
-
-	kv["llama4.feed_forward_length"] = p.TextModel.IntermediateSizeMLP
-	kv["llama4.expert_feed_forward_length"] = p.TextModel.IntermediateSize
-
-	kv["llama4.expert_count"] = p.TextModel.NumLocalExperts
-	kv["llama4.expert_used_count"] = p.TextModel.NumExpertsPerToken
-	kv["llama4.interleave_moe_layer_step"] = p.TextModel.InterleaveMOELayerStep
-	kv["llama4.use_qk_norm"] = p.TextModel.UseQKNorm
-	kv["llama4.attention.chunk_size"] = p.TextModel.AttentionChunkSize
-
-	kv["llama4.vision.block_count"] = p.VisionModel.NumHiddenLayers
-	kv["llama4.vision.embedding_length"] = p.VisionModel.HiddenSize
-	kv["llama4.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
-	kv["llama4.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
-	kv["llama4.vision.image_size"] = p.VisionModel.ImageSize
-	kv["llama4.vision.patch_size"] = p.VisionModel.PatchSize
-	kv["llama4.vision.rope.freq_base"] = p.VisionModel.RopeTheta
-	kv["llama4.vision.layer_norm_epsilon"] = p.VisionModel.NormEpsilon
-	kv["llama4.vision.pixel_shuffle_ratio"] = p.VisionModel.PixelShuffleRatio
-	return kv
-}
-
-// Replacements implements ModelConverter.
-func (p *llama4Model) Replacements() []string {
-	return append(
-		p.TextModel.Replacements(),
-		"language_model.", "",
-		"vision_model", "v",
-		"multi_modal_projector", "mm",
-		"feed_forward.down_proj", "ffn_down",
-		"feed_forward.up_proj", "ffn_up",
-		"feed_forward.gate_proj", "ffn_gate",
-		"feed_forward.", "ffn_",
-		"shared_expert.down_proj", "down_shexp",
-		"shared_expert.gate_proj", "gate_shexp",
-		"shared_expert.up_proj", "up_shexp",
-		"experts.down_proj", "down_exps.weight",
-		"experts.gate_up_proj", "gate_up_exps.weight",
-		"router", "gate_inp",
-		"patch_embedding.linear", "patch_embedding",
-	)
-}
-
-// Tensors implements ModelConverter.
-func (p *llama4Model) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-
-	var textTensors []Tensor
-	for _, t := range ts {
-		if strings.HasPrefix(t.Name(), "v.") || strings.HasPrefix(t.Name(), "mm.") {
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    t.Shape(),
-				WriterTo: t,
-			})
-		} else if strings.Contains(t.Name(), "ffn_gate_up_exps") {
-			// gate and up projectors are fused
-			// dims[1], dims[2] must be swapped
-			// [experts, hidden_size, intermediate_size * 2] --> [experts, intermediate_size, hidden_size]
-			halfDim := int(t.Shape()[2]) / 2
-
-			newShape := slices.Clone(t.Shape())
-			newShape[1], newShape[2] = newShape[2]/2, newShape[1]
-			for i, name := range []string{"ffn_gate_exps", "ffn_up_exps"} {
-				// clone tensor since we need separate repackers
-				tt := t.Clone()
-				tt.SetRepacker(p.repack(nil, nil, tensor.S(i*halfDim, (i+1)*halfDim)))
-				out = append(out, &ggml.Tensor{
-					Name:     strings.ReplaceAll(tt.Name(), "ffn_gate_up_exps", name),
-					Kind:     tt.Kind(),
-					Shape:    newShape,
-					WriterTo: tt,
-				})
-			}
-		} else if strings.Contains(t.Name(), "ffn_down_exps") {
-			// dims[1], dims[2] must be swapped
-			// [experts, intermediate_size, hidden_size] --> [experts, hidden_size, intermediate_size]
-			t.SetRepacker(p.repack())
-			newShape := slices.Clone(t.Shape())
-			newShape[1], newShape[2] = newShape[2], newShape[1]
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    newShape,
-				WriterTo: t,
-			})
-		} else {
-			textTensors = append(textTensors, t)
-		}
-	}
-
-	p.TextModel.skipRepack = true
-	out = append(out, p.TextModel.Tensors(textTensors)...)
-	return out
-}
-
-func (p *llama4Model) repack(slice ...tensor.Slice) Repacker {
-	return func(name string, data []float32, shape []uint64) ([]float32, error) {
-		dims := make([]int, len(shape))
-		for i, dim := range shape {
-			dims[i] = int(dim)
-		}
-
-		var t tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-		t, err := t.Slice(slice...)
-		if err != nil {
-			return nil, err
-		}
-
-		if err := t.T(0, 2, 1); err != nil {
-			return nil, err
-		}
-
-		t = tensor.Materialize(t)
-		// flatten tensor so it can be return as a vector
-		if err := t.Reshape(t.Shape().TotalSize()); err != nil {
-			return nil, err
-		}
-
-		return native.VectorF32(t.(*tensor.Dense))
-	}
-}

convert/convert_llama_adapter.go

@@ -7,7 +7,7 @@ import (
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type llamaAdapter struct {
@@ -18,7 +18,7 @@ type llamaAdapter struct {
 
 var _ AdapterConverter = (*llamaAdapter)(nil)
 
-func (p *llamaAdapter) KV(baseKV ggml.KV) ggml.KV {
+func (p *llamaAdapter) KV(baseKV fileutils.KV) fileutils.KV {
 	kv := p.AdapterParameters.KV()
 	kv["general.architecture"] = "llama"
 	kv["llama.attention.head_count"] = baseKV["llama.attention.head_count"]
@@ -29,8 +29,8 @@ func (p *llamaAdapter) KV(baseKV ggml.KV) ggml.KV {
 	return kv
 }
 
-func (p *llamaAdapter) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
+func (p *llamaAdapter) Tensors(ts []Tensor) []fileutils.Tensor {
+	var out []fileutils.Tensor
 	for _, t := range ts {
 		shape := t.Shape()
 		if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
@@ -41,7 +41,7 @@ func (p *llamaAdapter) Tensors(ts []Tensor) []*ggml.Tensor {
 			t.SetRepacker(p.repack)
 		}
 
-		out = append(out, &ggml.Tensor{
+		out = append(out, fileutils.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    shape,

convert/convert_mistral.go

@@ -1,190 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"fmt"
-	"strings"
-
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type mistral3Model struct {
-	ModelParameters
-	ImageTokenIndex    uint32 `json:"image_token_index"`
-	SpatialMergeSize   uint32 `json:"spatial_merge_size"`
-	VisionFeatureLayer int32  `json:"vision_feature_layer"`
-	TextModel          struct {
-		NumHiddenLayers       uint32  `json:"num_hidden_layers"`
-		MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-		HiddenSize            uint32  `json:"hidden_size"`
-		IntermediateSize      uint32  `json:"intermediate_size"`
-		NumAttentionHeads     uint32  `json:"num_attention_heads"`
-		NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-		RopeTheta             float32 `json:"rope_theta"`
-		RMSNormEPS            float32 `json:"rms_norm_eps"`
-		HeadDim               uint32  `json:"head_dim"`
-		SlidingWindow         *uint32 `json:"sliding_window"`
-		HiddenAct             string  `json:"hidden_act"`
-		VocabSize             uint32  `json:"vocab_size"`
-	} `json:"text_config"`
-	VisionModel struct {
-		NumAttentionHeads uint32  `json:"num_attention_heads"`
-		NumHiddenLayers   uint32  `json:"num_hidden_layers"`
-		HiddenSize        uint32  `json:"hidden_size"`
-		IntermediateSize  uint32  `json:"intermediate_size"`
-		ImageSize         uint32  `json:"image_size"`
-		NumChannels       uint32  `json:"num_channels"`
-		PatchSize         uint32  `json:"patch_size"`
-		HeadDim           uint32  `json:"head_dim"`
-		HiddenAct         string  `json:"hidden_act"`
-		RopeTheta         float32 `json:"rope_theta"`
-	} `json:"vision_config"`
-	MultiModalProjectorBias bool   `json:"multimodal_projector_bias"`
-	ProjectorHiddenAct      string `json:"projector_hidden_act"`
-}
-
-func (p *mistral3Model) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "mistral3"
-	kv["mistral3.vocab_size"] = p.TextModel.VocabSize
-
-	// Text configuration
-	kv["mistral3.block_count"] = p.TextModel.NumHiddenLayers
-	kv["mistral3.context_length"] = p.TextModel.MaxPositionEmbeddings
-	kv["mistral3.embedding_length"] = p.TextModel.HiddenSize
-	kv["mistral3.feed_forward_length"] = p.TextModel.IntermediateSize
-	kv["mistral3.attention.head_count"] = p.TextModel.NumAttentionHeads
-	kv["mistral3.attention.head_count_kv"] = p.TextModel.NumKeyValueHeads
-	kv["mistral3.attention.layer_norm_rms_epsilon"] = p.TextModel.RMSNormEPS
-	kv["mistral3.attention.key_length"] = p.TextModel.HeadDim
-	kv["mistral3.attention.value_length"] = p.TextModel.HeadDim
-	kv["mistral3.rope.dimension_count"] = p.TextModel.HiddenSize / p.TextModel.NumHiddenLayers
-	kv["mistral3.rope.freq_base"] = p.TextModel.RopeTheta
-
-	// Vision configuration
-	kv["mistral3.vision.block_count"] = p.VisionModel.NumHiddenLayers
-	kv["mistral3.vision.embedding_length"] = p.VisionModel.HiddenSize
-	kv["mistral3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
-	kv["mistral3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
-	kv["mistral3.vision.attention.key_length"] = p.VisionModel.HeadDim
-	kv["mistral3.vision.image_size"] = p.VisionModel.ImageSize
-	kv["mistral3.vision.patch_size"] = p.VisionModel.PatchSize
-	kv["mistral3.vision.num_channels"] = p.VisionModel.NumChannels
-	// kv["mistral3.vision.attention.layer_norm_epsilon"] = 1e-05 // Default value
-	kv["mistral3.vision.rope.freq_base"] = p.VisionModel.RopeTheta
-
-	// Multimodal configuration
-	kv["mistral3.image_token_index"] = p.ImageTokenIndex
-	kv["mistral3.spatial_merge_size"] = p.SpatialMergeSize
-
-	kv["mistral3.mm.projector_bias"] = p.MultiModalProjectorBias
-
-	if p.ProjectorHiddenAct != "" {
-		kv["mistral3.mm.projector_hidden_act"] = p.ProjectorHiddenAct
-	}
-
-	return kv
-}
-
-func (p *mistral3Model) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-
-	for _, t := range ts {
-		if !strings.HasPrefix(t.Name(), "v.") {
-			if strings.HasSuffix(t.Name(), ".attn_q.weight") ||
-				strings.HasSuffix(t.Name(), ".attn_k.weight") {
-				t.SetRepacker(p.repack)
-			}
-		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *mistral3Model) Replacements() []string {
-	return []string{
-		"language_model.model.norm", "output_norm",
-		"language_model.model.", "",
-		"language_model.", "",
-		"layers", "blk",
-		"transformer.layers", "blk",
-		"vision_tower", "v",
-		"ln_pre", "encoder_norm",
-		"input_layernorm", "attn_norm",
-		"post_attention_layernorm", "ffn_norm",
-		"embed_tokens", "token_embd",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.v_proj", "attn_v",
-		"self_attn.o_proj", "attn_output",
-		"mlp.down_proj", "ffn_down",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.up_proj", "ffn_up",
-		"attention.q_proj", "attn_q",
-		"attention.k_proj", "attn_k",
-		"attention.v_proj", "attn_v",
-		"attention.o_proj", "attn_output",
-		"attention_norm", "attn_norm",
-		"feed_forward.gate_proj", "ffn_gate",
-		"feed_forward.down_proj", "ffn_down",
-		"feed_forward.up_proj", "ffn_up",
-		"multi_modal_projector", "mm",
-		"ffn_norm", "ffn_norm",
-		"lm_head", "output",
-	}
-}
-
-func (p *mistral3Model) repack(name string, data []float32, shape []uint64) ([]float32, error) {
-	var dims []int
-	for _, dim := range shape {
-		dims = append(dims, int(dim))
-	}
-
-	var heads uint32
-	if strings.HasSuffix(name, ".attn_q.weight") {
-		heads = p.TextModel.NumAttentionHeads
-	} else if strings.HasSuffix(name, ".attn_k.weight") {
-		heads = cmp.Or(p.TextModel.NumKeyValueHeads, p.TextModel.NumAttentionHeads)
-	} else {
-		return nil, fmt.Errorf("unknown tensor for repack: %s", name)
-	}
-
-	n := tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-	if err := n.Reshape(append([]int{int(heads), 2, dims[0] / int(heads) / 2}, dims[1:]...)...); err != nil {
-		return nil, err
-	}
-
-	if err := n.T(0, 2, 1, 3); err != nil {
-		return nil, err
-	}
-
-	if err := n.Reshape(dims...); err != nil {
-		return nil, err
-	}
-
-	if err := n.Transpose(); err != nil {
-		return nil, err
-	}
-
-	ts, err := native.SelectF32(n, 1)
-	if err != nil {
-		return nil, err
-	}
-
-	var f32s []float32
-	for _, t := range ts {
-		f32s = append(f32s, t...)
-	}
-
-	return f32s, nil
-}

convert/convert_mixtral.go

@@ -2,8 +2,11 @@ package convert
 
 import (
 	"fmt"
+	"io"
+	"slices"
+	"strings"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type mixtralModel struct {
@@ -12,7 +15,7 @@ type mixtralModel struct {
 	NumExpertsPerToken uint32 `json:"num_experts_per_tok"`
 }
 
-func (p *mixtralModel) KV(t *Tokenizer) ggml.KV {
+func (p *mixtralModel) KV(t *Tokenizer) fileutils.KV {
 	kv := p.llamaModel.KV(t)
 
 	if p.NumLocalExperts > 0 {
@@ -26,39 +29,66 @@ func (p *mixtralModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p *mixtralModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	merges := make([]merge, 0, p.NumHiddenLayers*6)
-	for i := range p.NumHiddenLayers {
-		merges = append(merges, merge{
-			fmt.Sprintf("blk.%d.*.w1.weight", i),
-			fmt.Sprintf("blk.%d.ffn_gate_exps.weight", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w1.bias", i),
-			fmt.Sprintf("blk.%d.ffn_gate_exps.bias", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w2.weight", i),
-			fmt.Sprintf("blk.%d.ffn_up_exps.weight", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w2.bias", i),
-			fmt.Sprintf("blk.%d.ffn_up_exps.bias", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w3.weight", i),
-			fmt.Sprintf("blk.%d.ffn_down_exps.weight", i),
-		}, merge{
-			fmt.Sprintf("blk.%d.*.w3.bias", i),
-			fmt.Sprintf("blk.%d.ffn_down_exps.bias", i),
+func (p *mixtralModel) Tensors(ts []Tensor) []fileutils.Tensor {
+	oldnew := []string{
+		"model.layers", "blk",
+		"w1", "ffn_gate_exps",
+		"w2", "ffn_down_exps",
+		"w3", "ffn_up_exps",
+	}
+
+	for i := range p.NumLocalExperts {
+		oldnew = append(oldnew, fmt.Sprintf(".block_sparse_moe.experts.%d.", i), ".")
+	}
+
+	// group experts of the same layer (model.layers.%d) and type (w[123]) into a single tensor
+	namer := strings.NewReplacer(oldnew...)
+	experts := make(map[string]experts)
+
+	// merge experts into a single tensor while removing them from ts
+	ts = slices.DeleteFunc(ts, func(t Tensor) bool {
+		if !strings.Contains(t.Name(), ".block_sparse_moe.experts.") {
+			return false
+		}
+
+		name := namer.Replace(t.Name())
+		experts[name] = append(experts[name], t)
+		return true
+	})
+
+	var out []fileutils.Tensor
+	for n, e := range experts {
+		// TODO(mxyng): sanity check experts
+		out = append(out, fileutils.Tensor{
+			Name:     n,
+			Kind:     e[0].Kind(),
+			Shape:    append([]uint64{uint64(len(e))}, e[0].Shape()...),
+			WriterTo: e,
 		})
 	}
 
-	out, ts := mergeTensors(ts, merges...)
 	return append(out, p.llamaModel.Tensors(ts)...)
 }
 
 func (p *mixtralModel) Replacements() []string {
 	return append(
 		p.llamaModel.Replacements(),
-		"model.layers", "blk",
 		"block_sparse_moe.gate", "ffn_gate_inp",
-		"block_sparse_moe.experts.", ".",
 	)
 }
+
+type experts []Tensor
+
+func (e experts) WriteTo(w io.Writer) (int64, error) {
+	// TODO(mxyng): experts _should_ be numerically sorted by expert but this should check
+	for _, t := range e {
+		// the canonical merged experts tensor stacks all experts along a new, 0 axis,
+		// e.g. `tensor.Stack(0, e[0], e[1:]...)`, which requires allocating temporary buffers
+		// this accomplishes the same thing by writing each expert tensor in sequence
+		if _, err := t.WriteTo(w); err != nil {
+			return 0, err
+		}
+	}
+
+	return 0, nil
+}

convert/convert_mllama.go

@@ -1,179 +0,0 @@
-package convert
-
-import (
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-)
-
-type mllamaModel struct {
-	ModelParameters
-	TextModel struct {
-		llamaModel
-
-		CrossAttentionLayers []int32 `json:"cross_attention_layers"`
-	} `json:"text_config"`
-	VisionModel struct {
-		NumHiddenLayers           uint32  `json:"num_hidden_layers"`
-		NumGlobalLayers           uint32  `json:"num_global_layers"`
-		IntermediateLayersIndices []int32 `json:"intermediate_layers_indices"`
-
-		HiddenSize       uint32 `json:"hidden_size"`
-		IntermediateSize uint32 `json:"intermediate_size"`
-
-		AttentionHeads uint32 `json:"attention_heads"`
-
-		ImageSize   uint32  `json:"image_size"`
-		PatchSize   uint32  `json:"patch_size"`
-		NumChannels uint32  `json:"num_channels"`
-		MaxNumTiles uint32  `json:"max_num_tiles"`
-		NormEpsilon float32 `json:"norm_eps"`
-		RopeTheta   float32 `json:"rope.freq_base"`
-	} `json:"vision_config"`
-}
-
-func (m *mllamaModel) KV(t *Tokenizer) ggml.KV {
-	kv := m.ModelParameters.KV(t)
-	kv["general.architecture"] = "mllama"
-
-	for k, v := range m.TextModel.KV(t) {
-		if strings.HasPrefix(k, "llama.") {
-			kv[strings.ReplaceAll(k, "llama.", "mllama.")] = v
-		}
-	}
-
-	kv["mllama.attention.cross_attention_layers"] = m.TextModel.CrossAttentionLayers
-
-	kv["mllama.vision.block_count"] = m.VisionModel.NumHiddenLayers
-	kv["mllama.vision.global.block_count"] = m.VisionModel.NumGlobalLayers
-	kv["mllama.vision.intermediate_layers_indices"] = m.VisionModel.IntermediateLayersIndices
-
-	kv["mllama.vision.embedding_length"] = m.VisionModel.HiddenSize
-	kv["mllama.vision.feed_forward_length"] = m.VisionModel.IntermediateSize
-
-	kv["mllama.vision.attention.head_count"] = m.VisionModel.AttentionHeads
-	kv["mllama.vision.attention.layer_norm_epsilon"] = m.VisionModel.NormEpsilon
-
-	kv["mllama.vision.image_size"] = m.VisionModel.ImageSize
-	kv["mllama.vision.patch_size"] = m.VisionModel.PatchSize
-	kv["mllama.vision.max_num_tiles"] = m.VisionModel.MaxNumTiles
-	kv["mllama.vision.num_channels"] = m.VisionModel.NumChannels
-
-	return kv
-}
-
-func (m *mllamaModel) Replacements() []string {
-	return append(
-		m.TextModel.Replacements(),
-		"language_model.", "",
-		"gate_attn", "attn_gate",
-		"gate_ffn", "ffn_gate",
-		"cross_attn.", "cross_attn_",
-		"vision_model", "v",
-		"class_embedding", "class_embd",
-		"patch_embedding", "patch_embd",
-		"gated_positional_embedding.tile_embedding", "tile_position_embd",
-		"gated_positional_embedding.embedding", "position_embd.weight",
-		"gated_positional_embedding", "position_embd",
-		"embedding.weight", "weight",
-		"pre_tile_positional_embedding", "pre_tile_position_embd",
-		"post_tile_positional_embedding", "post_tile_position_embd",
-		"layernorm_pre", "pre_ln",
-		"layernorm_post", "post_ln",
-		"global_transformer.layers", "global.blk",
-		"transformer.layers", "blk",
-		"mlp.fc1", "ffn_up",
-		"mlp.fc2", "ffn_down",
-		"multi_modal_projector", "mm.0",
-	)
-}
-
-func (m *mllamaModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-	var text []Tensor
-	for _, t := range ts {
-		if !strings.HasPrefix(t.Name(), "v.") && !strings.HasPrefix(t.Name(), "mm.") {
-			text = append(text, t)
-		} else if t.Name() == "v.position_embd.gate" {
-			for _, name := range []string{"v.position_embd.gate", "v.tile_position_embd.gate"} {
-				tt := t.Clone()
-				tt.SetRepacker(m.repack(name))
-				out = append(out, &ggml.Tensor{
-					Name:     name,
-					Kind:     t.Kind(),
-					Shape:    t.Shape(),
-					WriterTo: tt,
-				})
-			}
-		} else {
-			if t.Name() == "v.pre_tile_position_embd.gate" || t.Name() == "v.post_tile_position_embd.gate" {
-				t.SetRepacker(m.repack(t.Name()))
-			} else if strings.HasSuffix(t.Name(), "attn_q.weight") || strings.HasSuffix(t.Name(), "attn_k.weight") {
-				t.SetRepacker(m.repack(t.Name()))
-			} else if strings.HasSuffix(t.Name(), "attn_gate") || strings.HasSuffix(t.Name(), "ffn_gate") {
-				t.SetRepacker(m.repack(t.Name()))
-			}
-
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    t.Shape(),
-				WriterTo: t,
-			})
-		}
-	}
-
-	return append(out, m.TextModel.Tensors(text)...)
-}
-
-func (m *mllamaModel) repack(name string) Repacker {
-	return func(_ string, data []float32, shape []uint64) (_ []float32, err error) {
-		dims := make([]int, len(shape))
-		for i, dim := range shape {
-			dims[i] = int(dim)
-		}
-
-		var t tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-
-		if strings.HasSuffix(name, "attn_q.weight") || strings.HasSuffix(name, "attn_k.weight") {
-			heads := m.VisionModel.AttentionHeads
-			if err := t.Reshape(append([]int{int(heads), 2, dims[0] / int(heads) / 2}, dims[1:]...)...); err != nil {
-				return nil, err
-			}
-
-			if err := t.T(0, 2, 1, 3); err != nil {
-				return nil, err
-			}
-
-			if err := t.Reshape(dims...); err != nil {
-				return nil, err
-			}
-
-			if err := t.Transpose(); err != nil {
-				return nil, err
-			}
-		} else {
-			t, err = tensor.Tanh(t)
-			if err != nil {
-				return nil, err
-			}
-
-			if name == "v.position_embd.gate" {
-				t, err = tensor.Sub(float32(1), t)
-				if err != nil {
-					return nil, err
-				}
-			}
-		}
-
-		t = tensor.Materialize(t)
-		// flatten tensor so it can be return as a vector
-		if err := t.Reshape(t.Shape().TotalSize()); err != nil {
-			return nil, err
-		}
-
-		return native.VectorF32(t.(*tensor.Dense))
-	}
-}

convert/convert_phi3.go

@@ -8,7 +8,7 @@ import (
 	"strings"
 	"sync"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fileutils"
 )
 
 type phi3Model struct {
@@ -37,7 +37,7 @@ type phi3Model struct {
 
 var _ ModelConverter = (*phi3Model)(nil)
 
-func (p *phi3Model) KV(t *Tokenizer) ggml.KV {
+func (p *phi3Model) KV(t *Tokenizer) fileutils.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "phi3"
 	kv["phi3.context_length"] = p.MaxPositionEmbeddings
@@ -68,19 +68,19 @@ func (p *phi3Model) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p *phi3Model) Tensors(ts []Tensor) []*ggml.Tensor {
+func (p *phi3Model) Tensors(ts []Tensor) []fileutils.Tensor {
 	var addRopeFactors sync.Once
 
-	out := make([]*ggml.Tensor, 0, len(ts)+2)
+	out := make([]fileutils.Tensor, 0, len(ts)+2)
 	for _, t := range ts {
 		if strings.HasPrefix(t.Name(), "blk.0.") {
 			addRopeFactors.Do(func() {
-				out = append(out, &ggml.Tensor{
+				out = append(out, fileutils.Tensor{
 					Name:     "rope_factors_long.weight",
 					Kind:     0,
 					Shape:    []uint64{uint64(len(p.RopeScaling.LongFactor))},
 					WriterTo: p.RopeScaling.LongFactor,
-				}, &ggml.Tensor{
+				}, fileutils.Tensor{
 					Name:     "rope_factors_short.weight",
 					Kind:     0,
 					Shape:    []uint64{uint64(len(p.RopeScaling.ShortFactor))},
@@ -89,7 +89,7 @@ func (p *phi3Model) Tensors(ts []Tensor) []*ggml.Tensor {
 			})
 		}
 
-		out = append(out, &ggml.Tensor{
+		out = append(out, fileutils.Tensor{
 			Name:     t.Name(),
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
@@ -118,5 +118,6 @@ func (p *phi3Model) Replacements() []string {
 type ropeFactor []float32
 
 func (r ropeFactor) WriteTo(w io.Writer) (int64, error) {
-	return 0, binary.Write(w, binary.LittleEndian, r)
+	err := binary.Write(w, binary.LittleEndian, r)
+	return 0, err
 }

convert/convert_qwen2.go

@@ -1,81 +0,0 @@
-package convert
-
-import "github.com/ollama/ollama/fs/ggml"
-
-type qwen2Model struct {
-	ModelParameters
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	HiddenLayers          uint32  `json:"num_hidden_layers"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	NumAttentionHeads     uint32  `json:"num_attention_heads"`
-	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-	RopeTheta             float32 `json:"rope_theta"`
-	RopeScaling           struct {
-		Type                          string     `json:"type"`
-		Factor                        ropeFactor `json:"factor"`
-		OriginalMaxPositionEmbeddings uint32     `json:"original_max_position_embeddings"`
-		MropeSection                  []int32    `json:"mrope_section"`
-	} `json:"rope_scaling"`
-	RMSNormEPS float32 `json:"rms_norm_eps"`
-}
-
-var _ ModelConverter = (*qwen2Model)(nil)
-
-func (q *qwen2Model) KV(t *Tokenizer) ggml.KV {
-	kv := q.ModelParameters.KV(t)
-	kv["general.architecture"] = "qwen2"
-	kv["qwen2.block_count"] = q.HiddenLayers
-	kv["qwen2.context_length"] = q.MaxPositionEmbeddings
-	kv["qwen2.embedding_length"] = q.HiddenSize
-	kv["qwen2.feed_forward_length"] = q.IntermediateSize
-	kv["qwen2.attention.head_count"] = q.NumAttentionHeads
-	kv["qwen2.attention.head_count_kv"] = q.NumKeyValueHeads
-	kv["qwen2.rope.freq_base"] = q.RopeTheta
-	kv["qwen2.attention.layer_norm_rms_epsilon"] = q.RMSNormEPS
-
-	switch q.RopeScaling.Type {
-	case "":
-		// no scaling
-	case "yarn":
-		kv["qwen2.rope.scaling.type"] = q.RopeScaling.Type
-		kv["qwen2.rope.scaling.factor"] = q.RopeScaling.Factor
-	case "mrope", "default":
-		kv["qwen2.rope.mrope_section"] = q.RopeScaling.MropeSection
-	default:
-		panic("unknown rope scaling type")
-	}
-	return kv
-}
-
-func (q *qwen2Model) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-	for _, t := range ts {
-		out = append(out, &ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *qwen2Model) Replacements() []string {
-	return []string{
-		"lm_head", "output",
-		"model.embed_tokens", "token_embd",
-		"model.layers", "blk",
-		"input_layernorm", "attn_norm",
-		"self_attn.k_proj", "attn_k",
-		"self_attn.v_proj", "attn_v",
-		"self_attn.q_proj", "attn_q",
-		"self_attn.o_proj", "attn_output",
-		"mlp.down_proj", "ffn_down",
-		"mlp.gate_proj", "ffn_gate",
-		"mlp.up_proj", "ffn_up",
-		"post_attention_layernorm", "ffn_norm",
-		"model.norm", "output_norm",
-	}
-}

convert/convert_qwen25vl.go

@@ -1,102 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type qwen25VLModel struct {
-	qwen2Model
-
-	VisionModel struct {
-		Depth               uint32  `json:"depth"`
-		HiddenSize          uint32  `json:"hidden_size"`
-		NumHeads            uint32  `json:"num_heads"`
-		InChannels          uint32  `json:"in_chans"`
-		PatchSize           uint32  `json:"patch_size"`
-		SpatialMergeSize    uint32  `json:"spatial_merge_size"`
-		SpatialPatchSize    uint32  `json:"spatial_patch_size"`
-		WindowSize          uint32  `json:"window_size"`
-		RMSNormEps          float32 `json:"layer_norm_epsilon"`
-		RopeTheta           float32 `json:"rope_theta"`
-		FullAttentionBlocks []int32 `json:"fullatt_block_indexes"`
-		TemporalPatchSize   uint32  `json:"temporal_patch_size"`
-	} `json:"vision_config"`
-}
-
-var _ ModelConverter = (*qwen25VLModel)(nil)
-
-func (q *qwen25VLModel) KV(t *Tokenizer) ggml.KV {
-	kv := q.ModelParameters.KV(t)
-	kv["general.architecture"] = "qwen25vl"
-
-	for k, v := range q.qwen2Model.KV(t) {
-		if strings.HasPrefix(k, "qwen2.") {
-			kv[strings.Replace(k, "qwen2.", "qwen25vl.", 1)] = v
-		}
-	}
-
-	if q.VisionModel.FullAttentionBlocks == nil {
-		kv["qwen25vl.vision.fullatt_block_indexes"] = []int32{7, 15, 23, 31}
-	}
-
-	kv["qwen25vl.vision.block_count"] = cmp.Or(q.VisionModel.Depth, 32)
-	kv["qwen25vl.vision.embedding_length"] = q.VisionModel.HiddenSize
-	kv["qwen25vl.vision.attention.head_count"] = cmp.Or(q.VisionModel.NumHeads, 16)
-	kv["qwen25vl.vision.num_channels"] = q.VisionModel.InChannels
-	kv["qwen25vl.vision.patch_size"] = cmp.Or(q.VisionModel.PatchSize, 14)
-	kv["qwen25vl.vision.spatial_merge_size"] = cmp.Or(q.VisionModel.SpatialMergeSize, 2)
-	kv["qwen25vl.vision.spatial_patch_size"] = q.VisionModel.SpatialPatchSize
-	kv["qwen25vl.vision.window_size"] = cmp.Or(q.VisionModel.WindowSize, 112)
-	kv["qwen25vl.vision.attention.layer_norm_epsilon"] = cmp.Or(q.VisionModel.RMSNormEps, 1e-6)
-	kv["qwen25vl.vision.rope.freq_base"] = cmp.Or(q.VisionModel.RopeTheta, 1e4)
-	kv["qwen25vl.vision.fullatt_block_indexes"] = q.VisionModel.FullAttentionBlocks
-	kv["qwen25vl.vision.temporal_patch_size"] = cmp.Or(q.VisionModel.TemporalPatchSize, 2)
-
-	return kv
-}
-
-func (q *qwen25VLModel) Tensors(ts []Tensor) []*ggml.Tensor {
-	var out []*ggml.Tensor
-
-	for _, t := range ts {
-		if strings.Contains(t.Name(), "patch_embed.proj") {
-			for t := range splitDim(t, 2,
-				split{Replacer: strings.NewReplacer("patch_embed.proj", "patch_embd_0")},
-				split{Replacer: strings.NewReplacer("patch_embed.proj", "patch_embd_1")},
-			) {
-				t.Shape = slices.DeleteFunc(t.Shape, func(i uint64) bool { return i == 1 })
-				out = append(out, t)
-			}
-		} else if strings.Contains(t.Name(), "attn.qkv") {
-			out = append(out, slices.Collect(splitDim(t, 0,
-				split{Replacer: strings.NewReplacer("attn.qkv", "attn_q")},
-				split{Replacer: strings.NewReplacer("attn.qkv", "attn_k")},
-				split{Replacer: strings.NewReplacer("attn.qkv", "attn_v")},
-			))...)
-		} else {
-			out = append(out, &ggml.Tensor{
-				Name:     t.Name(),
-				Kind:     t.Kind(),
-				Shape:    t.Shape(),
-				WriterTo: t,
-			})
-		}
-	}
-
-	return out
-}
-
-func (p *qwen25VLModel) Replacements() []string {
-	return append(
-		p.qwen2Model.Replacements(),
-		"visual", "v",
-		"blocks", "blk",
-		"attn.proj", "attn_out",
-		"norm1", "ln1",
-		"norm2", "ln2",
-	)
-}

convert/convert_test.go

@@ -11,14 +11,16 @@ import (
 	"io"
 	"io/fs"
 	"log/slog"
-	"maps"
+	"math"
 	"os"
 	"path/filepath"
 	"slices"
 	"strings"
 	"testing"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"golang.org/x/exp/maps"
+
+	"github.com/ollama/ollama/fileutils"
 )
 
 type tensorData struct {
@@ -27,7 +29,7 @@ type tensorData struct {
 	Shape   []int  `json:"shape"`
 }
 
-func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
+func convertFull(t *testing.T, fsys fs.FS) (*os.File, fileutils.KV, *fileutils.Tensors) {
 	t.Helper()
 
 	f, err := os.CreateTemp(t.TempDir(), "f16")
@@ -46,7 +48,7 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
 	}
 	t.Cleanup(func() { r.Close() })
 
-	m, err := ggml.Decode(r, -1)
+	m, _, err := fileutils.DecodeGGML(r, math.MaxInt)
 	if err != nil {
 		t.Fatal(err)
 	}
@@ -58,7 +60,7 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
 	return r, m.KV(), m.Tensors()
 }
 
-func generateResultsJSON(t *testing.T, f *os.File, kv ggml.KV, tensors ggml.Tensors) map[string]string {
+func generateResultsJSON(t *testing.T, f *os.File, kv fileutils.KV, tensors *fileutils.Tensors) map[string]string {
 	actual := make(map[string]string)
 	for k, v := range kv {
 		if s, ok := v.(json.Marshaler); !ok {
@@ -73,7 +75,7 @@ func generateResultsJSON(t *testing.T, f *os.File, kv ggml.KV, tensors ggml.Tens
 		}
 	}
 
-	for _, tensor := range tensors.Items() {
+	for _, tensor := range tensors.Items {
 		sha256sum := sha256.New()
 		sr := io.NewSectionReader(f, int64(tensors.Offset+tensor.Offset), int64(tensor.Size()))
 		if _, err := io.Copy(sha256sum, sr); err != nil {
@@ -106,8 +108,6 @@ func TestConvertModel(t *testing.T) {
 		"Phi-3-mini-128k-instruct",
 		"all-MiniLM-L6-v2",
 		"gemma-2-9b-it",
-		"Qwen2.5-0.5B-Instruct",
-		"c4ai-command-r-v01",
 	}
 
 	for i := range cases {
@@ -129,14 +129,15 @@ func TestConvertModel(t *testing.T) {
 			if err != nil {
 				t.Fatal(err)
 			}
-			defer expectFile.Close()
 
 			var expect map[string]string
 			if err := json.NewDecoder(expectFile).Decode(&expect); err != nil {
 				t.Fatal(err)
 			}
 
-			for _, k := range slices.Sorted(maps.Keys(expect)) {
+			keys := maps.Keys(expect)
+			slices.Sort(keys)
+			for _, k := range keys {
 				if v, ok := actual[k]; !ok {
 					t.Errorf("missing %s", k)
 				} else if v != expect[k] {
@@ -329,7 +330,7 @@ func TestConvertAdapter(t *testing.T) {
 			}
 			defer r.Close()
 
-			m, err := ggml.Decode(r, -1)
+			m, _, err := fileutils.DecodeGGML(r, math.MaxInt)
 			if err != nil {
 				t.Fatal(err)
 			}
@@ -340,7 +341,9 @@ func TestConvertAdapter(t *testing.T) {
 
 			actual := generateResultsJSON(t, r, m.KV(), m.Tensors())
 
-			for _, k := range slices.Sorted(maps.Keys(c.Expected)) {
+			keys := maps.Keys(c.Expected)
+			slices.Sort(keys)
+			for _, k := range keys {
 				if v, ok := actual[k]; !ok {
 					t.Errorf("missing %s", k)
 				} else if v != c.Expected[k] {

convert/fs.go

@@ -0,0 +1,58 @@
+package convert
+
+import (
+	"archive/zip"
+	"errors"
+	"io"
+	"io/fs"
+	"os"
+	"path/filepath"
+)
+
+type ZipReader struct {
+	r *zip.Reader
+	p string
+
+	// limit is the maximum size of a file that can be read directly
+	// from the zip archive. Files larger than this size will be extracted
+	limit int64
+}
+
+func NewZipReader(r *zip.Reader, p string, limit int64) fs.FS {
+	return &ZipReader{r, p, limit}
+}
+
+func (z *ZipReader) Open(name string) (fs.File, error) {
+	r, err := z.r.Open(name)
+	if err != nil {
+		return nil, err
+	}
+	defer r.Close()
+
+	if fi, err := r.Stat(); err != nil {
+		return nil, err
+	} else if fi.Size() < z.limit {
+		return r, nil
+	}
+
+	if !filepath.IsLocal(name) {
+		return nil, zip.ErrInsecurePath
+	}
+
+	n := filepath.Join(z.p, name)
+	if _, err := os.Stat(n); errors.Is(err, os.ErrNotExist) {
+		w, err := os.Create(n)
+		if err != nil {
+			return nil, err
+		}
+		defer w.Close()
+
+		if _, err := io.Copy(w, r); err != nil {
+			return nil, err
+		}
+	} else if err != nil {
+		return nil, err
+	}
+
+	return os.Open(n)
+}

convert/reader.go

@@ -11,15 +11,14 @@ type Tensor interface {
 	Name() string
 	Shape() []uint64
 	Kind() uint32
-	SetRepacker(Repacker)
+	SetRepacker(repacker)
 	WriteTo(io.Writer) (int64, error)
-	Clone() Tensor
 }
 
 type tensorBase struct {
-	name     string
-	shape    []uint64
-	repacker Repacker
+	name  string
+	shape []uint64
+	repacker
 }
 
 func (t tensorBase) Name() string {
@@ -31,46 +30,42 @@ func (t tensorBase) Shape() []uint64 {
 }
 
 const (
-	tensorKindFP32 uint32 = iota
-	tensorKindFP16
-	tensorKindBF16  = 30
-	tensorKindMXFP4 = 39
+	tensorKindF32 uint32 = iota
+	tensorKindF16
 )
 
 func (t tensorBase) Kind() uint32 {
 	if strings.HasSuffix(t.name, ".ffn_gate_inp.weight") ||
-		strings.HasSuffix(t.name, ".bias") ||
-		t.name == "token_types.weight" ||
-		t.name == "v.positional_embedding_vlm" ||
-		t.name == "v.tile_position_embd.weight" ||
-		t.name == "v.pre_tile_position_embd.weight" ||
-		t.name == "v.post_tile_position_embd.weight" {
+		t.name == "token_types.weight" {
 		// these tensors are always F32
-		return tensorKindFP32
+		return 0
 	}
 
 	switch len(t.shape) {
 	case 0:
 		panic("invalid tensor shape")
 	case 1:
-		return tensorKindFP32
+		return tensorKindF32
 	default:
-		return tensorKindFP16
+		return tensorKindF16
 	}
 }
 
-func (t *tensorBase) SetRepacker(fn Repacker) {
+func (t *tensorBase) SetRepacker(fn repacker) {
 	t.repacker = fn
 }
 
-type Repacker func(string, []float32, []uint64) ([]float32, error)
+type repacker func(string, []float32, []uint64) ([]float32, error)
 
 func parseTensors(fsys fs.FS, replacer *strings.Replacer) ([]Tensor, error) {
 	patterns := []struct {
 		Pattern string
 		Func    func(fs.FS, *strings.Replacer, ...string) ([]Tensor, error)
 	}{
-		{"*.safetensors", parseSafetensors},
+		{"model-*-of-*.safetensors", parseSafetensors},
+		{"model.safetensors", parseSafetensors},
+		{"adapters.safetensors", parseSafetensors},
+		{"adapter_model.safetensors", parseSafetensors},
 		{"pytorch_model-*-of-*.bin", parseTorch},
 		{"pytorch_model.bin", parseTorch},
 		{"consolidated.*.pth", parseTorch},

convert/reader_safetensors.go

@@ -1,7 +1,6 @@
 package convert
 
 import (
-	"bufio"
 	"bytes"
 	"encoding/binary"
 	"encoding/json"
@@ -9,12 +8,12 @@ import (
 	"fmt"
 	"io"
 	"io/fs"
-	"maps"
 	"slices"
 	"strings"
 
 	"github.com/d4l3k/go-bfloat16"
 	"github.com/x448/float16"
+	"golang.org/x/exp/maps"
 )
 
 type safetensorMetadata struct {
@@ -47,7 +46,8 @@ func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]T
 			return nil, err
 		}
 
-		keys := slices.Sorted(maps.Keys(headers))
+		keys := maps.Keys(headers)
+		slices.Sort(keys)
 
 		names := make(map[string]struct{}, len(keys))
 
@@ -94,30 +94,6 @@ type safetensor struct {
 	*tensorBase
 }
 
-func (st safetensor) Kind() uint32 {
-	kind := st.tensorBase.Kind()
-	if st.dtype == "BF16" && kind != tensorKindFP32 {
-		kind = tensorKindBF16
-	}
-
-	return kind
-}
-
-func (st safetensor) Clone() Tensor {
-	return &safetensor{
-		fs:     st.fs,
-		path:   st.path,
-		dtype:  st.dtype,
-		offset: st.offset,
-		size:   st.size,
-		tensorBase: &tensorBase{
-			name:     st.name,
-			repacker: st.repacker,
-			shape:    slices.Clone(st.shape),
-		},
-	}
-}
-
 func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 	f, err := st.fs.Open(st.path)
 	if err != nil {
@@ -125,41 +101,26 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 	}
 	defer f.Close()
 
-	r, err := func() (io.Reader, error) {
-		if readerAt, ok := f.(io.ReaderAt); ok {
-			return io.NewSectionReader(readerAt, st.offset, st.size), nil
-		} else if seeker, ok := f.(io.Seeker); ok {
-			_, err := seeker.Seek(st.offset, io.SeekStart)
-			return f, err
-		} else {
-			_, err := io.CopyN(io.Discard, f, st.offset)
-			return f, err
+	if seeker, ok := f.(io.Seeker); ok {
+		if _, err := seeker.Seek(st.offset, io.SeekStart); err != nil {
+			return 0, err
+		}
+	} else {
+		if _, err := io.CopyN(io.Discard, f, st.offset); err != nil {
+			return 0, err
 		}
-	}()
-	if err != nil {
-		return 0, err
-	}
-
-	br := bufio.NewReaderSize(r, min(32<<10, int(st.size)))
-	// special case when input and output are same type and the
-	// tensor doesn't need repacking
-	if (st.repacker == nil) &&
-		((st.dtype == "F32" && st.Kind() == tensorKindFP32) ||
-			(st.dtype == "F16" && st.Kind() == tensorKindFP16) ||
-			(st.dtype == "U8")) {
-		return io.CopyN(w, br, st.size)
 	}
 
 	var f32s []float32
 	switch st.dtype {
 	case "F32":
 		f32s = make([]float32, st.size/4)
-		if err = binary.Read(br, binary.LittleEndian, f32s); err != nil {
+		if err = binary.Read(f, binary.LittleEndian, f32s); err != nil {
 			return 0, err
 		}
 	case "F16":
 		u16s := make([]uint16, st.size/2)
-		if err = binary.Read(br, binary.LittleEndian, u16s); err != nil {
+		if err = binary.Read(f, binary.LittleEndian, u16s); err != nil {
 			return 0, err
 		}
 
@@ -170,7 +131,7 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 
 	case "BF16":
 		u8s := make([]uint8, st.size)
-		if err = binary.Read(br, binary.LittleEndian, u8s); err != nil {
+		if err = binary.Read(f, binary.LittleEndian, u8s); err != nil {
 			return 0, err
 		}
 
@@ -187,18 +148,15 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 	}
 
 	switch st.Kind() {
-	case tensorKindFP32:
-		return int64(len(f32s) * 4), binary.Write(w, binary.LittleEndian, f32s)
-	case tensorKindFP16:
+	case tensorKindF32:
+		return 0, binary.Write(w, binary.LittleEndian, f32s)
+	case tensorKindF16:
 		f16s := make([]uint16, len(f32s))
 		for i := range f32s {
 			f16s[i] = float16.Fromfloat32(f32s[i]).Bits()
 		}
 
-		return int64(len(f16s) * 2), binary.Write(w, binary.LittleEndian, f16s)
-	case tensorKindBF16:
-		u8s := bfloat16.EncodeFloat32(f32s)
-		return int64(len(u8s)), binary.Write(w, binary.LittleEndian, u8s)
+		return 0, binary.Write(w, binary.LittleEndian, f16s)
 	default:
 		return 0, fmt.Errorf("unknown storage type: %d", st.Kind())
 	}

convert/reader_test.go

@@ -1,232 +0,0 @@
-package convert
-
-import (
-	"bytes"
-	"encoding/binary"
-	"os"
-	"path/filepath"
-	"testing"
-
-	"github.com/d4l3k/go-bfloat16"
-	"github.com/google/go-cmp/cmp"
-	"github.com/x448/float16"
-)
-
-func TestSafetensors(t *testing.T) {
-	t.Parallel()
-
-	root, err := os.OpenRoot(t.TempDir())
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer root.Close()
-
-	cases := []struct {
-		name,
-		dtype string
-		offset,
-		size int64
-		shape []uint64
-		setup func(*testing.T, *os.File)
-		want  []byte
-	}{
-		{
-			name:  "fp32-fp32",
-			dtype: "F32",
-			size:  32 * 4, // 32 floats, each 4 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, f32s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x3f, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x40, 0x40,
-				0x00, 0x00, 0x80, 0x40, 0x00, 0x00, 0xa0, 0x40, 0x00, 0x00, 0xc0, 0x40, 0x00, 0x00, 0xe0, 0x40,
-				0x00, 0x00, 0x00, 0x41, 0x00, 0x00, 0x10, 0x41, 0x00, 0x00, 0x20, 0x41, 0x00, 0x00, 0x30, 0x41,
-				0x00, 0x00, 0x40, 0x41, 0x00, 0x00, 0x50, 0x41, 0x00, 0x00, 0x60, 0x41, 0x00, 0x00, 0x70, 0x41,
-				0x00, 0x00, 0x80, 0x41, 0x00, 0x00, 0x88, 0x41, 0x00, 0x00, 0x90, 0x41, 0x00, 0x00, 0x98, 0x41,
-				0x00, 0x00, 0xa0, 0x41, 0x00, 0x00, 0xa8, 0x41, 0x00, 0x00, 0xb0, 0x41, 0x00, 0x00, 0xb8, 0x41,
-				0x00, 0x00, 0xc0, 0x41, 0x00, 0x00, 0xc8, 0x41, 0x00, 0x00, 0xd0, 0x41, 0x00, 0x00, 0xd8, 0x41,
-				0x00, 0x00, 0xe0, 0x41, 0x00, 0x00, 0xe8, 0x41, 0x00, 0x00, 0xf0, 0x41, 0x00, 0x00, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "fp32-fp16",
-			dtype: "F32",
-			size:  32 * 4, // 32 floats, each 4 bytes
-			shape: []uint64{16, 2},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, f32s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x3c, 0x00, 0x40, 0x00, 0x42, 0x00, 0x44, 0x00, 0x45, 0x00, 0x46, 0x00, 0x47,
-				0x00, 0x48, 0x80, 0x48, 0x00, 0x49, 0x80, 0x49, 0x00, 0x4a, 0x80, 0x4a, 0x00, 0x4b, 0x80, 0x4b,
-				0x00, 0x4c, 0x40, 0x4c, 0x80, 0x4c, 0xc0, 0x4c, 0x00, 0x4d, 0x40, 0x4d, 0x80, 0x4d, 0xc0, 0x4d,
-				0x00, 0x4e, 0x40, 0x4e, 0x80, 0x4e, 0xc0, 0x4e, 0x00, 0x4f, 0x40, 0x4f, 0x80, 0x4f, 0xc0, 0x4f,
-			},
-		},
-		{
-			name:  "fp16-fp16",
-			dtype: "F16",
-			size:  32 * 2, // 32 floats, each 2 bytes
-			shape: []uint64{16, 2},
-			setup: func(t *testing.T, f *os.File) {
-				u16s := make([]uint16, 32)
-				for i := range u16s {
-					u16s[i] = float16.Fromfloat32(float32(i)).Bits()
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, u16s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x3c, 0x00, 0x40, 0x00, 0x42, 0x00, 0x44, 0x00, 0x45, 0x00, 0x46, 0x00, 0x47,
-				0x00, 0x48, 0x80, 0x48, 0x00, 0x49, 0x80, 0x49, 0x00, 0x4a, 0x80, 0x4a, 0x00, 0x4b, 0x80, 0x4b,
-				0x00, 0x4c, 0x40, 0x4c, 0x80, 0x4c, 0xc0, 0x4c, 0x00, 0x4d, 0x40, 0x4d, 0x80, 0x4d, 0xc0, 0x4d,
-				0x00, 0x4e, 0x40, 0x4e, 0x80, 0x4e, 0xc0, 0x4e, 0x00, 0x4f, 0x40, 0x4f, 0x80, 0x4f, 0xc0, 0x4f,
-			},
-		},
-		{
-			name:  "fp16-fp32",
-			dtype: "F16",
-			size:  32 * 2, // 32 floats, each 2 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				u16s := make([]uint16, 32)
-				for i := range u16s {
-					u16s[i] = float16.Fromfloat32(float32(i)).Bits()
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, u16s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x3f, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x40, 0x40,
-				0x00, 0x00, 0x80, 0x40, 0x00, 0x00, 0xa0, 0x40, 0x00, 0x00, 0xc0, 0x40, 0x00, 0x00, 0xe0, 0x40,
-				0x00, 0x00, 0x00, 0x41, 0x00, 0x00, 0x10, 0x41, 0x00, 0x00, 0x20, 0x41, 0x00, 0x00, 0x30, 0x41,
-				0x00, 0x00, 0x40, 0x41, 0x00, 0x00, 0x50, 0x41, 0x00, 0x00, 0x60, 0x41, 0x00, 0x00, 0x70, 0x41,
-				0x00, 0x00, 0x80, 0x41, 0x00, 0x00, 0x88, 0x41, 0x00, 0x00, 0x90, 0x41, 0x00, 0x00, 0x98, 0x41,
-				0x00, 0x00, 0xa0, 0x41, 0x00, 0x00, 0xa8, 0x41, 0x00, 0x00, 0xb0, 0x41, 0x00, 0x00, 0xb8, 0x41,
-				0x00, 0x00, 0xc0, 0x41, 0x00, 0x00, 0xc8, 0x41, 0x00, 0x00, 0xd0, 0x41, 0x00, 0x00, 0xd8, 0x41,
-				0x00, 0x00, 0xe0, 0x41, 0x00, 0x00, 0xe8, 0x41, 0x00, 0x00, 0xf0, 0x41, 0x00, 0x00, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "bf16-bf16",
-			dtype: "BF16",
-			size:  32 * 2, // 32 brain floats, each 2 bytes
-			shape: []uint64{16, 2},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, bfloat16.EncodeFloat32(f32s)); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x80, 0x3f, 0x00, 0x40, 0x40, 0x40, 0x80, 0x40, 0xa0, 0x40, 0xc0, 0x40, 0xe0, 0x40,
-				0x00, 0x41, 0x10, 0x41, 0x20, 0x41, 0x30, 0x41, 0x40, 0x41, 0x50, 0x41, 0x60, 0x41, 0x70, 0x41,
-				0x80, 0x41, 0x88, 0x41, 0x90, 0x41, 0x98, 0x41, 0xa0, 0x41, 0xa8, 0x41, 0xb0, 0x41, 0xb8, 0x41,
-				0xc0, 0x41, 0xc8, 0x41, 0xd0, 0x41, 0xd8, 0x41, 0xe0, 0x41, 0xe8, 0x41, 0xf0, 0x41, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "bf16-fp32",
-			dtype: "BF16",
-			size:  32 * 2, // 32 brain floats, each 2 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				f32s := make([]float32, 32)
-				for i := range f32s {
-					f32s[i] = float32(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, bfloat16.EncodeFloat32(f32s)); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x80, 0x3f, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x40, 0x40,
-				0x00, 0x00, 0x80, 0x40, 0x00, 0x00, 0xa0, 0x40, 0x00, 0x00, 0xc0, 0x40, 0x00, 0x00, 0xe0, 0x40,
-				0x00, 0x00, 0x00, 0x41, 0x00, 0x00, 0x10, 0x41, 0x00, 0x00, 0x20, 0x41, 0x00, 0x00, 0x30, 0x41,
-				0x00, 0x00, 0x40, 0x41, 0x00, 0x00, 0x50, 0x41, 0x00, 0x00, 0x60, 0x41, 0x00, 0x00, 0x70, 0x41,
-				0x00, 0x00, 0x80, 0x41, 0x00, 0x00, 0x88, 0x41, 0x00, 0x00, 0x90, 0x41, 0x00, 0x00, 0x98, 0x41,
-				0x00, 0x00, 0xa0, 0x41, 0x00, 0x00, 0xa8, 0x41, 0x00, 0x00, 0xb0, 0x41, 0x00, 0x00, 0xb8, 0x41,
-				0x00, 0x00, 0xc0, 0x41, 0x00, 0x00, 0xc8, 0x41, 0x00, 0x00, 0xd0, 0x41, 0x00, 0x00, 0xd8, 0x41,
-				0x00, 0x00, 0xe0, 0x41, 0x00, 0x00, 0xe8, 0x41, 0x00, 0x00, 0xf0, 0x41, 0x00, 0x00, 0xf8, 0x41,
-			},
-		},
-		{
-			name:  "u8-u8",
-			dtype: "U8",
-			size:  32, // 32 brain floats, each 1 bytes
-			shape: []uint64{32},
-			setup: func(t *testing.T, f *os.File) {
-				u8s := make([]uint8, 32)
-				for i := range u8s {
-					u8s[i] = uint8(i)
-				}
-
-				if err := binary.Write(f, binary.LittleEndian, u8s); err != nil {
-					t.Fatal(err)
-				}
-			},
-			want: []byte{
-				0x00, 0x01, 0x02, 0x03, 0x04, 0x05, 0x06, 0x07, 0x08, 0x09, 0x0a, 0x0b, 0x0c, 0x0d, 0x0e, 0x0f,
-				0x10, 0x11, 0x12, 0x13, 0x14, 0x15, 0x16, 0x17, 0x18, 0x19, 0x1a, 0x1b, 0x1c, 0x1d, 0x1e, 0x1f,
-			},
-		},
-	}
-
-	for _, tt := range cases {
-		t.Run(tt.name, func(t *testing.T) {
-			path := filepath.Base(t.Name())
-			st := safetensor{
-				fs:     root.FS(),
-				path:   path,
-				dtype:  tt.dtype,
-				offset: tt.offset,
-				size:   tt.size,
-				tensorBase: &tensorBase{
-					name:  tt.name,
-					shape: tt.shape,
-				},
-			}
-
-			f, err := root.Create(path)
-			if err != nil {
-				t.Fatal(err)
-			}
-			defer f.Close()
-
-			tt.setup(t, f)
-
-			var b bytes.Buffer
-			if _, err := st.WriteTo(&b); err != nil {
-				t.Fatal(err)
-			}
-
-			if diff := cmp.Diff(tt.want, b.Bytes()); diff != "" {
-				t.Errorf("safetensor.WriteTo() mismatch (-want +got):\n%s", diff)
-			}
-		})
-	}
-}

convert/reader_torch.go

@@ -43,17 +43,6 @@ type torch struct {
 	*tensorBase
 }
 
-func (t torch) Clone() Tensor {
-	return torch{
-		storage: t.storage,
-		tensorBase: &tensorBase{
-			name:     t.name,
-			shape:    t.shape,
-			repacker: t.repacker,
-		},
-	}
-}
-
 func (pt torch) WriteTo(w io.Writer) (int64, error) {
 	return 0, nil
 }

convert/sentencepiece/sentencepiece_model.pb.go

@@ -331,7 +331,7 @@ type TrainerSpec struct {
 	// Reserved special meta tokens.
 	// * -1 is not used.
 	// * unk_id must not be -1.
-	// Id must start with 0 and be contiguous.
+	// Id must starts with 0 and be contigous.
 	UnkId    *int32  `protobuf:"varint,40,opt,name=unk_id,json=unkId,def=0" json:"unk_id,omitempty"`  // <unk>
 	BosId    *int32  `protobuf:"varint,41,opt,name=bos_id,json=bosId,def=1" json:"bos_id,omitempty"`  // <s>
 	EosId    *int32  `protobuf:"varint,42,opt,name=eos_id,json=eosId,def=2" json:"eos_id,omitempty"`  // </s>
@@ -1360,7 +1360,7 @@ func file_sentencepiece_model_proto_rawDescGZIP() []byte {
 
 var file_sentencepiece_model_proto_enumTypes = make([]protoimpl.EnumInfo, 2)
 var file_sentencepiece_model_proto_msgTypes = make([]protoimpl.MessageInfo, 6)
-var file_sentencepiece_model_proto_goTypes = []any{
+var file_sentencepiece_model_proto_goTypes = []interface{}{
 	(TrainerSpec_ModelType)(0),         // 0: sentencepiece.TrainerSpec.ModelType
 	(ModelProto_SentencePiece_Type)(0), // 1: sentencepiece.ModelProto.SentencePiece.Type
 	(*TrainerSpec)(nil),                // 2: sentencepiece.TrainerSpec
@@ -1392,7 +1392,7 @@ func file_sentencepiece_model_proto_init() {
 		return
 	}
 	if !protoimpl.UnsafeEnabled {
-		file_sentencepiece_model_proto_msgTypes[0].Exporter = func(v any, i int) any {
+		file_sentencepiece_model_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
 			switch v := v.(*TrainerSpec); i {
 			case 0:
 				return &v.state
@@ -1406,7 +1406,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[1].Exporter = func(v any, i int) any {
+		file_sentencepiece_model_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
 			switch v := v.(*NormalizerSpec); i {
 			case 0:
 				return &v.state
@@ -1420,7 +1420,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[2].Exporter = func(v any, i int) any {
+		file_sentencepiece_model_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
 			switch v := v.(*SelfTestData); i {
 			case 0:
 				return &v.state
@@ -1434,7 +1434,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[3].Exporter = func(v any, i int) any {
+		file_sentencepiece_model_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
 			switch v := v.(*ModelProto); i {
 			case 0:
 				return &v.state
@@ -1448,7 +1448,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[4].Exporter = func(v any, i int) any {
+		file_sentencepiece_model_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
 			switch v := v.(*SelfTestData_Sample); i {
 			case 0:
 				return &v.state
@@ -1460,7 +1460,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[5].Exporter = func(v any, i int) any {
+		file_sentencepiece_model_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
 			switch v := v.(*ModelProto_SentencePiece); i {
 			case 0:
 				return &v.state

convert/sentencepiece_model.proto

@@ -213,7 +213,7 @@ message TrainerSpec {
   // Reserved special meta tokens.
   // * -1 is not used.
   // * unk_id must not be -1.
-  // Id must start with 0 and be contiguous.
+  // Id must starts with 0 and be contigous.
   optional int32 unk_id = 40 [default = 0];   // <unk>
   optional int32 bos_id = 41 [default = 1];   // <s>
   optional int32 eos_id = 42 [default = 2];   // </s>

convert/tensor.go

@@ -1,129 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"io"
-	"iter"
-	"path"
-	"slices"
-	"strings"
-
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type split struct {
-	*strings.Replacer
-	dim int
-
-	// fn is an optional function to apply to the tensor after slicing
-	fn func(tensor.Tensor) (tensor.Tensor, error)
-}
-
-// splitDim splits a tensor along a specified dimension into multiple tensors. The dimension
-// is split evenly based on the number of replacers provided unless a specific count is given.
-func splitDim(t Tensor, dim int, splits ...split) iter.Seq[*ggml.Tensor] {
-	return func(yield func(*ggml.Tensor) bool) {
-		var offset int
-		for _, split := range splits {
-			t := t.Clone()
-			shape := slices.Clone(t.Shape())
-			shape[dim] = cmp.Or(uint64(split.dim), shape[dim]/uint64(len(splits)))
-
-			slice := slices.Repeat([]tensor.Slice{nil}, len(shape))
-			slice[dim] = tensor.S(offset, offset+int(shape[dim]))
-			offset += int(shape[dim])
-
-			t.SetRepacker(func(_ string, data []float32, shape []uint64) ([]float32, error) {
-				dims := make([]int, len(shape))
-				for i := range shape {
-					dims[i] = int(shape[i])
-				}
-
-				var tt tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-				tt, err := tt.Slice(slice...)
-				if err != nil {
-					return nil, err
-				}
-
-				tt = tensor.Materialize(tt)
-
-				if split.fn != nil {
-					tt, err = split.fn(tt)
-					if err != nil {
-						return nil, err
-					}
-				}
-
-				// flatten tensor so it can be written as a vector
-				if err := tt.Reshape(tt.Shape().TotalSize()); err != nil {
-					return nil, err
-				}
-
-				return native.VectorF32(tt.(*tensor.Dense))
-			})
-
-			if !yield(&ggml.Tensor{
-				Name:     split.Replace(t.Name()),
-				Kind:     t.Kind(),
-				Shape:    shape,
-				WriterTo: t,
-			}) {
-				break
-			}
-		}
-	}
-}
-
-type merge struct {
-	pattern, name string
-}
-
-// mergeTensors merges tensors that match a given pattern into a single tensor.
-func mergeTensors(unmatched []Tensor, merges ...merge) (out []*ggml.Tensor, _ []Tensor) {
-	var matched []Tensor
-	for i := range merges {
-		matched, unmatched = slicesSplitFunc(unmatched, func(t Tensor) bool {
-			matched, _ := path.Match(merges[i].pattern, t.Name())
-			return matched
-		})
-
-		if len(matched) > 0 {
-			out = append(out, &ggml.Tensor{
-				Name:     merges[i].name,
-				Kind:     matched[0].Kind(),
-				Shape:    append([]uint64{uint64(len(matched))}, matched[0].Shape()...),
-				WriterTo: mergeGroup(matched),
-			})
-		}
-	}
-
-	return out, unmatched
-}
-
-// slicesSplitFunc splits a slice into two slices based on a predicate function.
-func slicesSplitFunc[S ~[]E, E comparable](s S, fn func(e E) bool) (matched, unmatched S) {
-	for _, e := range s {
-		if fn(e) {
-			matched = append(matched, e)
-		} else {
-			unmatched = append(unmatched, e)
-		}
-	}
-
-	return matched, unmatched
-}
-
-type mergeGroup []Tensor
-
-func (g mergeGroup) WriteTo(w io.Writer) (int64, error) {
-	for _, t := range g {
-		if _, err := t.WriteTo(w); err != nil {
-			return 0, err
-		}
-	}
-
-	return 0, nil
-}

convert/tensor_test.go

@@ -1,953 +0,0 @@
-package convert
-
-import (
-	"bytes"
-	"encoding/binary"
-	"io"
-	"iter"
-	"slices"
-	"strings"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/pdevine/tensor"
-)
-
-type fakeTensor struct {
-	name  string
-	shape []uint64
-	data  []float32
-
-	repacker Repacker
-}
-
-func (f fakeTensor) Name() string {
-	return f.name
-}
-
-func (f fakeTensor) Shape() []uint64 {
-	return f.shape
-}
-
-func (f fakeTensor) Kind() uint32 {
-	return 0
-}
-
-func (f *fakeTensor) SetRepacker(fn Repacker) {
-	f.repacker = fn
-}
-
-func (f fakeTensor) Clone() Tensor {
-	return &fakeTensor{
-		name:     f.name,
-		shape:    slices.Clone(f.shape),
-		data:     slices.Clone(f.data),
-		repacker: f.repacker,
-	}
-}
-
-func (f fakeTensor) WriteTo(w io.Writer) (n int64, err error) {
-	data := f.data
-	if f.repacker != nil {
-		data, err = f.repacker(f.name, data, f.shape)
-		if err != nil {
-			return 0, err
-		}
-	}
-
-	if err := binary.Write(w, binary.LittleEndian, data); err != nil {
-		return 0, err
-	}
-
-	return int64(len(data) * 4), nil
-}
-
-func mul(shape []uint64) int {
-	n := 1
-	for _, dim := range shape {
-		n *= int(dim)
-	}
-	return n
-}
-
-func TestSplitDim(t *testing.T) {
-	t.Run("2d", func(t *testing.T) {
-		r := fakeTensor{
-			name:  "a.b",
-			shape: []uint64{3, 4},
-			data:  []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11},
-		}
-
-		t.Run("no split", func(t *testing.T) {
-			for tt := range splitDim(&r, 0, split{Replacer: strings.NewReplacer("a", "x")}) {
-				if tt.Name != "x.b" {
-					t.Fatalf("expected name 'x', got '%s'", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("even split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x")},
-				split{Replacer: strings.NewReplacer("b", "y")},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 4, 5, 8, 9}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{2, 3, 6, 7, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{2, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{8, 9, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{4, 5, 6, 7}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{8, 9, 10, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 4, 5, 8, 9}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{2, 6, 10}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{3, 7, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("split with transpose", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x")},
-				split{Replacer: strings.NewReplacer("b", "y"), fn: func(tt tensor.Tensor) (tensor.Tensor, error) {
-					return tensor.Transpose(tt, 1, 0)
-				}},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 4, 5, 8, 9}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{2, 6, 10, 3, 7, 11}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-	})
-	t.Run("3d", func(t *testing.T) {
-		r := fakeTensor{
-			name:  "a.b",
-			shape: []uint64{3, 4, 2},
-			data:  []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23},
-		}
-
-		t.Run("no split", func(t *testing.T) {
-			for tt := range splitDim(&r, 0, split{Replacer: strings.NewReplacer("a", "x")}) {
-				if tt.Name != "x.b" {
-					t.Fatalf("expected name 'x', got '%s'", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("even split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x")},
-				split{Replacer: strings.NewReplacer("b", "y")},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{2, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'a.y', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{16, 17, 18, 19, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 0,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{8, 9, 10, 11, 12, 13, 14, 15}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{1, 4, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{16, 17, 18, 19, 20, 21, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-
-		t.Run("uneven three way split", func(t *testing.T) {
-			next, stop := iter.Pull(splitDim(&r, 1,
-				split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
-				split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
-				split{Replacer: strings.NewReplacer("b", "z"), dim: 1},
-			))
-			defer stop()
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "x.b" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 2, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.y" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{4, 5, 12, 13, 20, 21}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-
-			{
-				tt, ok := next()
-				if !ok {
-					t.Fatal("expected at least one split")
-				}
-
-				if tt.Name != "a.z" {
-					t.Fatal("expected name 'x.b', got", tt.Name)
-				}
-
-				if diff := cmp.Diff(tt.Shape, []uint64{3, 1, 2}); diff != "" {
-					t.Errorf("unexpected shape (-want +got):\n%s", diff)
-				}
-
-				var b bytes.Buffer
-				if _, err := tt.WriteTo(&b); err != nil {
-					t.Fatal(err)
-				}
-
-				f32s := make([]float32, mul(tt.Shape))
-				if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-					t.Fatal(err)
-				}
-
-				if diff := cmp.Diff(f32s, []float32{6, 7, 14, 15, 22, 23}); diff != "" {
-					t.Errorf("unexpected data (-want +got):\n%s", diff)
-				}
-			}
-		})
-	})
-}
-
-func TestMerge(t *testing.T) {
-	unmatched := []Tensor{
-		&fakeTensor{
-			name:  "a.0.b",
-			shape: []uint64{5, 2},
-			data:  []float32{10, 11, 12, 13, 14, 15, 16, 17, 18, 19},
-		},
-		&fakeTensor{
-			name:  "a.1.b",
-			shape: []uint64{5, 2},
-			data:  []float32{20, 21, 22, 23, 24, 25, 26, 27, 28, 29},
-		},
-		&fakeTensor{
-			name:  "c.0.d",
-			shape: []uint64{5, 2},
-			data:  []float32{30, 31, 32, 33, 34, 35, 36, 37, 38, 39},
-		},
-		&fakeTensor{
-			name:  "c.1.d",
-			shape: []uint64{5, 2},
-			data:  []float32{40, 41, 42, 43, 44, 45, 46, 47, 48, 49},
-		},
-		&fakeTensor{
-			name:  "e.0.f",
-			shape: []uint64{5, 2},
-			data:  []float32{50, 51, 52, 53, 54, 55, 56, 57, 58, 59},
-		},
-	}
-
-	checkMatched := func(t *testing.T, n int, matched []*ggml.Tensor) {
-		for i := range n {
-			got := matched[i]
-			if diff := cmp.Diff([]uint64{2, 5, 2}, got.Shape); diff != "" {
-				t.Errorf("unexpected (-want +got):\n%s", diff)
-			}
-
-			var b bytes.Buffer
-			if _, err := got.WriteTo(&b); err != nil {
-				t.Fatal(err)
-			}
-
-			f32s := make([]float32, 20)
-			if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
-				t.Fatal(err)
-			}
-
-			offset := 10 + (i * 20)
-			want := make([]float32, 20)
-			for j := range 20 {
-				want[j] = float32(offset + j)
-			}
-
-			if diff := cmp.Diff(want, f32s); diff != "" {
-				t.Errorf("unexpected data (-want +got):\n%s", diff)
-			}
-		}
-	}
-
-	t.Run("single merge", func(t *testing.T) {
-		matched, unmatched := mergeTensors(unmatched, merge{"a.*.b", "a.b"})
-		if len(unmatched) != 3 {
-			t.Error("expected 3 remaining tensors, got", len(unmatched))
-		}
-
-		if len(matched) != 1 {
-			t.Error("expected 1 merged tensor, got", len(matched))
-		}
-
-		checkMatched(t, 1, matched)
-	})
-
-	t.Run("multiple merges", func(t *testing.T) {
-		matched, unmatched := mergeTensors(unmatched, merge{"a.*.b", "a.b"}, merge{"c.*.d", "c.d"})
-		if len(unmatched) != 1 {
-			t.Error("expected 1 remaining tensors, got", len(unmatched))
-		}
-
-		if len(matched) != 2 {
-			t.Error("expected 2 merged tensor, got", len(matched))
-		}
-
-		checkMatched(t, 2, matched)
-	})
-
-	t.Run("no match", func(t *testing.T) {
-		matched, unmatched := mergeTensors(unmatched, merge{"x.*.y", "x.y"})
-		if len(unmatched) != 5 {
-			t.Error("expected 5 remaining tensors, got", len(unmatched))
-		}
-
-		if len(matched) != 0 {
-			t.Error("expected no merged tensors, got", len(matched))
-		}
-	})
-}

convert/testdata/Qwen2.5-0.5B-Instruct.json

@@ -1,314 +0,0 @@
-{
-    "general.architecture": "qwen2",
-    "general.file_type": "1",
-    "general.parameter_count": "494032768",
-    "general.quantization_version": "2",
-    "output_norm.weight": "93a01a6db3419e85320a244bbf8ae81c43033b1d10c342bea3797ff2ce348390",
-    "qwen2.attention.head_count": "14",
-    "qwen2.attention.head_count_kv": "2",
-    "qwen2.attention.layer_norm_rms_epsilon": "1e-06",
-    "qwen2.block_count": "24",
-    "qwen2.context_length": "32768",
-    "qwen2.embedding_length": "896",
-    "qwen2.feed_forward_length": "4864",
-    "qwen2.rope.freq_base": "1e+06",
-    "token_embd.weight": "d74257dc547b48be5ae7b93f1c9af072c0c42dbbb85503078e25c59cd09e68d0",
-    "tokenizer.ggml.add_eos_token": "false",
-    "tokenizer.ggml.add_padding_token": "false",
-    "tokenizer.ggml.eos_token_id": "151645",
-    "tokenizer.ggml.merges": "6b1b1c58f1223d74f9095929d3e6416cdd74784440221a5507b87b8197f2bfd2",
-    "tokenizer.ggml.model": "gpt2",
-    "tokenizer.ggml.padding_token_id": "151643",
-    "tokenizer.ggml.pre": "qwen2",
-    "tokenizer.ggml.scores": "94e247e531e8b0fa3d248f3de09c9beae0c87da8106208a8edfaac0b8ec4b53d",
-    "tokenizer.ggml.token_type": "b178dbc9d1b2e08f84d02918e00fc2de2619a250e6c188c91a6605f701860055",
-    "tokenizer.ggml.tokens": "1d93f6679b23a1152b725f7f473792d54d53c1040c5250d3e46b42f81e0a1a34",
-    "blk.0.attn_k.bias": "5ce6617845f66c34515978d23d52e729c298d8bffa28c356a0428bef17142cf1",
-    "blk.0.attn_k.weight": "a960832a9e0e83e4d95402e5d1a01cc74300fcca0c381237162126330e1a7af8",
-    "blk.0.attn_norm.weight": "32c7d51cd0958f1f1771174192db341f9770516d7595a2f0fd18a4d78bd5aba3",
-    "blk.0.attn_output.weight": "c67e6e7e868354a11bf9121c70ee56c140b20eec611a8955e7dfe54a21d40a98",
-    "blk.0.attn_q.bias": "3e9e994eb1f03bccfc82f8bb3c324c920d42d547e07de5be83be12c428645063",
-    "blk.0.attn_q.weight": "dc12132f789b97cfa1e3f5775ceb835247fa67aa47400fd09c8f9f3769208583",
-    "blk.0.attn_v.bias": "a3fd0757b31fdc78af5ec320332d239c1a79d34e8804df06c5454e86955e8cc9",
-    "blk.0.attn_v.weight": "f43094a2134c7ee2dcc52aac3c8b7d9d64fb0295a8adb94cabfd49213f017b84",
-    "blk.0.ffn_down.weight": "18c2aec92db14f21976838a8c35d5575f80d0e4b1e05ccc0d8388d5877e80147",
-    "blk.0.ffn_gate.weight": "a3a1c4ef38f8f750eabadfe3d83bbb0f77941eec1cc1a388e51852e99c8691f6",
-    "blk.0.ffn_norm.weight": "b59b779c42d44b5c4cec41e39b4eb61e0491a07c1b3e946ccb5b8d5c657eda3f",
-    "blk.0.ffn_up.weight": "db64f09987ea59449e90abae5a2ffcc20efd9203f0eebec77a6aacb5809d6cff",
-    "blk.1.attn_k.bias": "a5c8c5671703ec0aa0143ff70a20ffdd67b5d5790ca1dfa5bba4e87e4071ed9f",
-    "blk.1.attn_k.weight": "835c7c7cc95b3cb2e55bd9cac585aa0760a033896621d3e06421f3378c540f7d",
-    "blk.1.attn_norm.weight": "f4c36fb6c14fce721fab0de78cc118d6f66e3a3d3ea0017bb14aade24c3c5434",
-    "blk.1.attn_output.weight": "cc1e80310c97cef068e48e40b7096f32fa2138519d6209c6a1a9994985999016",
-    "blk.1.attn_q.bias": "bc332780e66b0aac80ec5e63ac32344919a840db2fcc8f87bcef16a43a54138e",
-    "blk.1.attn_q.weight": "d766f06c925cce38d4b31b2165b3448e1fb49a7d561985f95d9cd2fcba52367a",
-    "blk.1.attn_v.bias": "9f486626fb6ed9ac84970a71e9b9818dd2758501fd3f61bb1c08540dcc7a8631",
-    "blk.1.attn_v.weight": "e873d1e5bd4f4d6abfd47c0f55119c2c111105838753ee273a03c5ccea25ce5c",
-    "blk.1.ffn_down.weight": "b3ce82b093f187344de04284b1783a452de1b72640914609b8f830dc81580521",
-    "blk.1.ffn_gate.weight": "5cd44ad237edaca525a28a3ac13975d1b565f576d6a8003237a341ae0d156f2e",
-    "blk.1.ffn_norm.weight": "4ac774ee8afaee119610c46aa1ff89fc6c9084a29d226075bc4aa4d2f15f746c",
-    "blk.1.ffn_up.weight": "042d81ab5f1983d85c81213232f3bfc05a9302d9dfaa98d931ebba326b6058b8",
-    "blk.10.attn_k.bias": "767ecfeacd60a2c2221ac4d76c357190849dd9cdf64ced418d9d0c7949101401",
-    "blk.10.attn_k.weight": "a9f3df343227537636be8202303453086375091944e498bad11e0b91e45e8c71",
-    "blk.10.attn_norm.weight": "01acd0e7b3e363f873dbfde6f0995ffcce83f5aaa10ff91c31dbf775035f6d5a",
-    "blk.10.attn_output.weight": "a531fe660769604ab869f01b203eb115e025cad4c0baeacdd1bcca99cf6d0264",
-    "blk.10.attn_q.bias": "356a02c9163dd660c1340fbe1e049b335ac6178891e00996131bba9ab4cb3e59",
-    "blk.10.attn_q.weight": "81be0cfb227339d83f954cd8dcf35828441211c6e1d184060e3eb76085041e2f",
-    "blk.10.attn_v.bias": "ed0450653284b62f8bf2c2db19c0ff7a6cf3cda1324d0a044c5e3db7bb692bd3",
-    "blk.10.attn_v.weight": "c1247ff7092babd2ed979883095b9aa022b2996cab1c77fb9e6176ddc1498d16",
-    "blk.10.ffn_down.weight": "fda7544965dc9af874f1062c22151c6cefc8ba08cbe15dc67aa89979e77b2de4",
-    "blk.10.ffn_gate.weight": "9f2632b1dee7304d10c70bd38d85bb1f148a628a8468f894f57975b8a2f1d945",
-    "blk.10.ffn_norm.weight": "94f8cbd6b17a4d5aabd93fa32930a687db3b11f086142f1cd71c535c11adcad4",
-    "blk.10.ffn_up.weight": "8dc2f8db0474939a277a3d89db34c3bcc3381cfea57bd05a8426a164634d9112",
-    "blk.11.attn_k.bias": "3b8e5a662b19411e3f6530714b766aad2ee41eebc8161bec9db0bc82d383a6e0",
-    "blk.11.attn_k.weight": "2c29f1ed1ce53ce9604e9ea3663c2c373157e909a0d6064a8920005f6d15dad9",
-    "blk.11.attn_norm.weight": "48f68a99c3da4ab4c9e492677b606d1b8e0e3de1fdbf6a977523f97b8c21ec31",
-    "blk.11.attn_output.weight": "5859f3838a94898b020c23040941ed88f4fcb132db400d0849f30a01f62c0f1c",
-    "blk.11.attn_q.bias": "c5ad89a5628f2bd81252ef44ef6bbcbff15c33ad16fba66435509b959c2af6d3",
-    "blk.11.attn_q.weight": "d102104e5d61c1e3219564f1d0149fd593db6c6daa9f3872460c84403323cfef",
-    "blk.11.attn_v.bias": "8653f7d48c5f75a5b55630819f99ecf01c932f12d33fd1a3ee634613e70edde8",
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convert/testdata/c4ai-command-r-v01.json

@@ -1,344 +0,0 @@
-{
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-    "general.name": "command-r",
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-    "blk.39.ffn_down.weight": "4d9ee7c65fc16fe95d10c47b79ac6a525741947600a64b5fcea5d300a82c50de",
-    "blk.39.ffn_gate.weight": "7e18507989f39b32191133d2657c2ee3b74f42f070579204d727eb72215793d1",
-    "blk.39.ffn_up.weight": "22cda752269c9757ba918abede1df95bb0f83a5c772dea13c8deea3d5f2723d9",
-    "output_norm.weight": "2858cf0e39d32caf52b7861378ace076000241e147f10b9eb21d8a5cd149e3cb"
-}

convert/tokenizer.go

@@ -8,10 +8,10 @@ import (
 	"fmt"
 	"io/fs"
 	"log/slog"
-	"maps"
 	"os"
 	"slices"
-	"strings"
+
+	"golang.org/x/exp/maps"
 )
 
 const (
@@ -60,25 +60,7 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 			addedTokens[t.Content] = t
 		}
 
-		if len(tt.Model.Merges) == 0 {
-			// noop; merges is empty
-		} else if err := json.Unmarshal(tt.Model.Merges, &t.Merges); err == nil {
-			// noop; merges is []string
-		} else if merges, err := func() ([][]string, error) {
-			var merges [][]string
-			if err := json.Unmarshal(tt.Model.Merges, &merges); err != nil {
-				return nil, err
-			}
-
-			return merges, nil
-		}(); err == nil {
-			t.Merges = make([]string, len(merges))
-			for i := range merges {
-				t.Merges[i] = strings.Join(merges[i], " ")
-			}
-		} else {
-			return nil, fmt.Errorf("could not parse tokenizer merges. expected []string or [][]string: %w", err)
-		}
+		t.Merges = tt.Model.Merges
 
 		sha256sum := sha256.New()
 		for _, pt := range tt.PreTokenizer.PreTokenizers {
@@ -99,8 +81,6 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 			t.Pre = "deepseek-llm"
 		case "21cde974d587f0d54dc8d56b183cc1e6239600172035c68fbd6d4b9f8da0576e":
 			t.Pre = "deepseek-coder"
-		case "1ff7f41064896984db5d1bb6ff64fa4bc29007d08c1b439e505b7392777a319e":
-			t.Pre = "qwen2"
 		case "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855":
 			// noop, empty pretokenizer
 		default:
@@ -109,7 +89,6 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 	}
 
 	if f, err := fsys.Open("tokenizer_config.json"); errors.Is(err, os.ErrNotExist) {
-		// noop
 	} else if err != nil {
 		return nil, err
 	} else {
@@ -171,43 +150,15 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 		}
 	}
 
-	if f, err := fsys.Open("generation_config.json"); errors.Is(err, os.ErrNotExist) {
-	} else if err != nil {
-		return nil, err
-	} else {
-		defer f.Close()
-
-		var p map[string]json.RawMessage
-		if err := json.NewDecoder(f).Decode(&p); err != nil {
-			return nil, err
-		}
-
-		for _, st := range specialTokenTypes {
-			if bts, ok := p[fmt.Sprintf("%s_token_id", st)]; ok {
-				var ids []int32
-				if err := json.Unmarshal(bts, &ids); err != nil {
-					// value is not a list so the existing ID is used
-					continue
-				}
-
-				if i := slices.IndexFunc(t.SpecialVocabulary, func(sv *SpecialVocabulary) bool {
-					return sv.Type == st
-				}); i >= 0 {
-					t.SpecialVocabulary[i].IDs = ids
-				}
-			}
-		}
-	}
-
 	return t, nil
 }
 
 type tokenizer struct {
 	AddedTokens []token `json:"added_tokens"`
 	Model       struct {
-		Type   string          `json:"type"`
-		Vocab  map[string]int  `json:"vocab"`
-		Merges json.RawMessage `json:"merges"`
+		Type   string         `json:"type"`
+		Vocab  map[string]int `json:"vocab"`
+		Merges []string       `json:"merges"`
 	} `json:"model"`
 
 	PreTokenizer struct {
@@ -259,8 +210,11 @@ func parseVocabularyFromTokenizer(fsys fs.FS) (*Vocabulary, error) {
 		tokens[token.ID] = token
 	}
 
+	keys := maps.Keys(tokens)
+	slices.Sort(keys)
+
 	v := Vocabulary{Model: "gpt2"}
-	for _, k := range slices.Sorted(maps.Keys(tokens)) {
+	for _, k := range keys {
 		token := tokens[k]
 		v.Tokens = append(v.Tokens, token.Content)
 		v.Scores = append(v.Scores, float32(token.ID))
@@ -305,9 +259,6 @@ type SpecialVocabulary struct {
 	ID       int
 	Content  string
 	AddToken bool
-
-	// IDs is populated by generation_config.json
-	IDs []int32
 }
 
 func (sv SpecialVocabulary) Key() string {

convert/tokenizer_spm.go

@@ -6,9 +6,7 @@ import (
 	"errors"
 	"fmt"
 	"io/fs"
-	"log/slog"
 	"os"
-	"reflect"
 	"slices"
 
 	"google.golang.org/protobuf/proto"
@@ -17,8 +15,6 @@ import (
 )
 
 func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
-	slog.Debug("using spm vocabulary")
-
 	ast, err := parseAdditionalSpecialTokens(fsys)
 	if err != nil {
 		return nil, err
@@ -47,19 +43,10 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 			v.Types = append(v.Types, int32(t))
 		default:
 			tt := int32(sentencepiece.ModelProto_SentencePiece_NORMAL)
-
-			// temporary fix to handle gemma3 broken configs
-			if slices.Contains([]string{"<end_of_turn>", "<start_of_turn>"}, piece.GetPiece()) {
+			if slices.Contains(ast, piece.GetPiece()) {
 				tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)
 			}
 
-			for _, t := range ast {
-				if t.Content == piece.GetPiece() {
-					tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)
-					break
-				}
-			}
-
 			v.Types = append(v.Types, tt)
 		}
 	}
@@ -91,16 +78,10 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 		return cmp.Compare(i.id, j.id)
 	})
 
-	for _, t := range ts {
-		if t.id < len(v.Tokens) {
-			if v.Tokens[t.id] == t.content {
-				slog.Warn("tokenizer", "duplicate token", t.content, "id", t.id)
-				continue
-			}
-			return nil, fmt.Errorf("token mismatch: %s != %s at pos [%d]", t.content, v.Tokens[t.id], t.id)
-		}
-		if t.id != len(v.Tokens) {
-			return nil, fmt.Errorf("invalid token id: [%d] as pos [%d]", t.id, len(v.Tokens))
+	n := len(v.Tokens)
+	for i, t := range ts {
+		if t.id != i+n {
+			return nil, fmt.Errorf("invalid token id: %d", t.id)
 		}
 
 		v.Tokens = append(v.Tokens, t.content)
@@ -111,15 +92,7 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 	return &v, nil
 }
 
-type specialToken struct {
-	Content    string `json:"content"`
-	Lstrip     bool   `json:"lstrip"`
-	Normalized bool   `json:"normalized"`
-	Rstrip     bool   `json:"rstrip"`
-	SingleWord bool   `json:"single_word"`
-}
-
-func parseAdditionalSpecialTokens(fsys fs.FS) ([]specialToken, error) {
+func parseAdditionalSpecialTokens(fsys fs.FS) ([]string, error) {
 	f, err := fsys.Open("special_tokens_map.json")
 	if errors.Is(err, os.ErrNotExist) {
 		return nil, nil
@@ -129,43 +102,12 @@ func parseAdditionalSpecialTokens(fsys fs.FS) ([]specialToken, error) {
 	defer f.Close()
 
 	var m struct {
-		AdditionalSpecialTokens any `json:"additional_special_tokens"`
+		AdditionalSpecialTokens []string `json:"additional_special_tokens"`
 	}
 
 	if err := json.NewDecoder(f).Decode(&m); err != nil {
 		return nil, err
 	}
 
-	var ast []specialToken
-
-	switch st := m.AdditionalSpecialTokens.(type) {
-	case []string:
-		for _, s := range st {
-			ast = append(ast, specialToken{Content: s})
-		}
-	case []any:
-		for _, s := range st {
-			// marshal and unmarshal the object to get the special token
-			tMap := s.(map[string]any)
-			data, err := json.Marshal(tMap)
-			if err != nil {
-				return nil, err
-			}
-
-			var token specialToken
-			err = json.Unmarshal(data, &token)
-			if err != nil {
-				return nil, err
-			}
-
-			ast = append(ast, token)
-		}
-
-	default:
-		slog.Warn("special token", "unknown token", reflect.TypeOf(st))
-	}
-
-	slog.Debug("spm tokenizer", "additional tokens", ast)
-
-	return ast, nil
+	return m.AdditionalSpecialTokens, nil
 }

convert/tokenizer_test.go

@@ -191,123 +191,6 @@ func TestParseTokenizer(t *testing.T) {
 				Pre: "default",
 			},
 		},
-		{
-			name: "list string merges",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{
-					"model": {
-						"merges": [
-							"a b",
-							"c d",
-							"e f"
-						]
-					}
-				}`),
-			}),
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{
-					Model: "gpt2",
-				},
-				Merges: []string{
-					"a b",
-					"c d",
-					"e f",
-				},
-				Pre: "default",
-			},
-		},
-		{
-			name: "list list string merges",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{
-					"model": {
-						"merges": [
-							[
-								"a", "b"
-							],
-							[
-								"c", "d"
-							],
-							[
-								"e", "f"
-							]
-						]
-					}
-				}`),
-			}),
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{
-					Model: "gpt2",
-				},
-				Merges: []string{
-					"a b",
-					"c d",
-					"e f",
-				},
-				Pre: "default",
-			},
-		},
-		{
-			name: "generation config eos token ids",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{
-					"added_tokens": [
-						{
-							"id": 0,
-							"content": "<bos>",
-							"special": true
-						},
-						{
-							"id": 1,
-							"content": "<eos>",
-							"special": true
-						},
-						{
-							"id": 2,
-							"content": "<eot>",
-							"special": true
-						},
-						{
-							"id": 3,
-							"content": "<eom>",
-							"special": true
-						}
-					],
-					"model": {
-						"vocab": {
-							"<bos>": 0,
-							"<eos>": 1,
-							"<eot>": 2,
-							"<eom>": 3
-						}
-					}
-				}`),
-				"tokenizer_config.json": strings.NewReader(`{
-					"add_bos_token": true,
-					"add_eos_token": false,
-					"bos_token": "<bos>",
-					"eos_token": "<eos>"
-				}`),
-				"generation_config.json": strings.NewReader(`{
-					"bos_token_id": 0,
-					"eos_token_id": [1, 2, 3]
-				}`),
-			}),
-			specialTokenTypes: []string{"pad", "eos", "bos", "unk"},
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{
-					Model:  "gpt2",
-					Tokens: []string{"<bos>", "<eos>", "<eot>", "<eom>"},
-					Scores: []float32{0, 1, 2, 3},
-					Types:  []int32{3, 3, 3, 3},
-				},
-				SpecialVocabulary: []*SpecialVocabulary{
-					{Type: "eos", Content: "<eos>", ID: 1, IDs: []int32{1, 2, 3}, AddToken: false},
-					{Type: "bos", Content: "<bos>", ID: 0, AddToken: true},
-				},
-				Pre: "default",
-			},
-		},
 	}
 
 	for _, tt := range cases {

discover/README.md

@@ -0,0 +1,3 @@
+# `discover`
+
+This package is responsible for discovering information about the system and the capabilities to run LLM.  This includes GPU and CPU discovery so the optimal runner can be chosen for a given model.  The ollama scheduler relies on up-to-date available memory information, so this package provides the ability to refresh free memory as efficiently as possible.

discover/amd_common.go

@@ -9,6 +9,8 @@ import (
 	"path/filepath"
 	"runtime"
 	"strings"
+
+	"github.com/ollama/ollama/envconfig"
 )
 
 // Determine if the given ROCm lib directory is usable by checking for existence of some glob patterns
@@ -35,14 +37,30 @@ func GetSupportedGFX(libDir string) ([]string, error) {
 	return ret, nil
 }
 
+func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
+	ids := []string{}
+	for _, info := range gpuInfo {
+		if info.Library != "rocm" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("rocmGetVisibleDevicesEnv skipping over non-rocm device", "library", info.Library)
+			continue
+		}
+		ids = append(ids, info.ID)
+	}
+	return "HIP_VISIBLE_DEVICES", strings.Join(ids, ",")
+}
+
 func commonAMDValidateLibDir() (string, error) {
 	// Favor our bundled version
 
 	// Installer payload location if we're running the installed binary
-	rocmTargetDir := filepath.Join(LibOllamaPath, "rocm")
-	if rocmLibUsable(rocmTargetDir) {
-		slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
-		return rocmTargetDir, nil
+	exe, err := os.Executable()
+	if err == nil {
+		rocmTargetDir := filepath.Join(filepath.Dir(exe), envconfig.LibRelativeToExe(), "lib", "ollama")
+		if rocmLibUsable(rocmTargetDir) {
+			slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
+			return rocmTargetDir, nil
+		}
 	}
 
 	// Prefer explicit HIP env var

discover/amd_hip_windows.go

@@ -64,7 +64,7 @@ func NewHipLib() (*HipLib, error) {
 	return hl, nil
 }
 
-// The hip library only evaluates the ROCR_VISIBLE_DEVICES variable at startup
+// The hip library only evaluates the HIP_VISIBLE_DEVICES variable at startup
 // so we have to unload/reset the library after we do our initial discovery
 // to make sure our updates to that variable are processed by llama.cpp
 func (hl *HipLib) Release() {

discover/amd_linux.go

@@ -58,26 +58,29 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 	driverMajor, driverMinor, err := AMDDriverVersion()
 	if err != nil {
 		// TODO - if we see users crash and burn with the upstreamed kernel this can be adjusted to hard-fail rocm support and fallback to CPU
-		slog.Warn("ollama recommends running the https://www.amd.com/en/support/download/linux-drivers.html", "error", err)
+		slog.Warn("ollama recommends running the https://www.amd.com/en/support/linux-drivers", "error", err)
 	}
 
 	// Determine if the user has already pre-selected which GPUs to look at, then ignore the others
 	var visibleDevices []string
 	hipVD := envconfig.HipVisibleDevices()   // zero based index only
-	rocrVD := envconfig.RocrVisibleDevices() // zero based index or UUID
+	rocrVD := envconfig.RocrVisibleDevices() // zero based index or UUID, but consumer cards seem to not support UUID
 	gpuDO := envconfig.GpuDeviceOrdinal()    // zero based index
 	switch {
-	case rocrVD != "":
-		visibleDevices = strings.Split(rocrVD, ",")
+	// TODO is this priorty order right?
 	case hipVD != "":
 		visibleDevices = strings.Split(hipVD, ",")
+	case rocrVD != "":
+		visibleDevices = strings.Split(rocrVD, ",")
+		// TODO - since we don't yet support UUIDs, consider detecting and reporting here
+		// all our test systems show GPU-XX indicating UUID is not supported
 	case gpuDO != "":
 		visibleDevices = strings.Split(gpuDO, ",")
 	}
 
 	gfxOverride := envconfig.HsaOverrideGfxVersion()
 	var supported []string
-	var libDir string
+	libDir := ""
 
 	// The amdgpu driver always exposes the host CPU(s) first, but we have to skip them and subtract
 	// from the other IDs to get alignment with the HIP libraries expectations (zero is the first GPU, not the CPU)
@@ -96,8 +99,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 		}
 		return a < b
 	})
-	gpuCount := 0
-	gpuOrdinalID := 0
+	cpuCount := 0
 	for _, match := range matches {
 		slog.Debug("evaluating amdgpu node " + match)
 		fp, err := os.Open(match)
@@ -106,6 +108,11 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 			continue
 		}
 		defer fp.Close()
+		nodeID, err := strconv.Atoi(filepath.Base(filepath.Dir(match)))
+		if err != nil {
+			slog.Debug("failed to parse node ID", "error", err)
+			continue
+		}
 
 		scanner := bufio.NewScanner(fp)
 		isCPU := false
@@ -179,13 +186,18 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 		// do reliably report VRAM usage.
 
 		if isCPU {
+			cpuCount++
 			continue
 		}
 
-		// Skip over any GPUs that are masked
-		if major == 0 && minor == 0 && patch == 0 {
-			slog.Debug("skipping gpu with gfx000")
-			continue
+		// CPUs are always first in the list
+		gpuID := nodeID - cpuCount
+
+		// Shouldn't happen, but just in case...
+		if gpuID < 0 {
+			err := fmt.Errorf("unexpected amdgpu sysfs data resulted in negative GPU ID, please set OLLAMA_DEBUG=1 and report an issue")
+			slog.Error(err.Error())
+			return nil, err
 		}
 
 		// Look up the memory for the current node
@@ -261,14 +273,6 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 			name = fmt.Sprintf("%04x:%04x", vendor, device)
 		}
 
-		// Favor UUIDs if available to reduce possibility of getting the numeric IDs wrong
-		var ID string
-		if uniqueID != 0 {
-			ID = fmt.Sprintf("GPU-%016x", uniqueID)
-		} else {
-			ID = strconv.Itoa(gpuOrdinalID)
-		}
-
 		gpuInfo := RocmGPUInfo{
 			GpuInfo: GpuInfo{
 				Library: "rocm",
@@ -276,8 +280,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 					TotalMemory: totalMemory,
 					FreeMemory:  (totalMemory - usedMemory),
 				},
-				ID:            ID,
-				filterID:      gpuOrdinalID,
+				ID:            strconv.Itoa(gpuID),
 				Name:          name,
 				Compute:       fmt.Sprintf("gfx%d%x%x", major, minor, patch),
 				MinimumMemory: rocmMinimumMemory,
@@ -285,24 +288,45 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 				DriverMinor:   driverMinor,
 			},
 			usedFilepath: usedFile,
-			index:        gpuCount,
 		}
 
-		// Keep track of numeric IDs based on valid GPUs
-		gpuCount += 1
+		// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
+		if totalMemory < IGPUMemLimit {
+			reason := "unsupported Radeon iGPU detected skipping"
+			slog.Info(reason, "id", gpuID, "total", format.HumanBytes2(totalMemory))
+			unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
+				GpuInfo: gpuInfo.GpuInfo,
+				Reason:  reason,
+			})
+			continue
+		}
+
+		if int(major) < RocmComputeMin {
+			reason := fmt.Sprintf("amdgpu too old gfx%d%x%x", major, minor, patch)
+			slog.Warn(reason, "gpu", gpuID)
+			unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
+				GpuInfo: gpuInfo.GpuInfo,
+				Reason:  reason,
+			})
+
+			continue
+		}
+
+		slog.Debug("amdgpu memory", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
+		slog.Debug("amdgpu memory", "gpu", gpuID, "available", format.HumanBytes2(totalMemory-usedMemory))
 
 		// If the user wants to filter to a subset of devices, filter out if we aren't a match
 		if len(visibleDevices) > 0 {
 			include := false
 			for _, visible := range visibleDevices {
-				if (uniqueID != 0 && visible == gpuInfo.ID) || visible == strconv.Itoa(gpuInfo.index) {
+				if visible == gpuInfo.ID {
 					include = true
 					break
 				}
 			}
 			if !include {
 				reason := "filtering out device per user request"
-				slog.Info(reason, "id", gpuInfo.ID, "index", gpuInfo.index, "visible_devices", visibleDevices)
+				slog.Info(reason, "id", gpuInfo.ID, "visible_devices", visibleDevices)
 				unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
 					GpuInfo: gpuInfo.GpuInfo,
 					Reason:  reason,
@@ -312,37 +336,6 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 			}
 		}
 
-		// Ordinal IDs are based on the visible GPUs
-		gpuOrdinalID += 1
-
-		// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
-		if totalMemory < IGPUMemLimit {
-			reason := "unsupported Radeon iGPU detected skipping"
-			slog.Info(reason, "id", gpuInfo.ID, "total", format.HumanBytes2(totalMemory))
-			unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
-				GpuInfo: gpuInfo.GpuInfo,
-				Reason:  reason,
-			})
-			continue
-		}
-		minVer, err := strconv.Atoi(RocmComputeMajorMin)
-		if err != nil {
-			slog.Error("invalid RocmComputeMajorMin setting", "value", RocmComputeMajorMin, "error", err)
-		}
-		if int(major) < minVer {
-			reason := fmt.Sprintf("amdgpu too old gfx%d%x%x", major, minor, patch)
-			slog.Warn(reason, "gpu", gpuInfo.ID)
-			unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
-				GpuInfo: gpuInfo.GpuInfo,
-				Reason:  reason,
-			})
-
-			continue
-		}
-
-		slog.Debug("amdgpu memory", "gpu", gpuInfo.ID, "total", format.HumanBytes2(totalMemory))
-		slog.Debug("amdgpu memory", "gpu", gpuInfo.ID, "available", format.HumanBytes2(totalMemory-usedMemory))
-
 		// Final validation is gfx compatibility - load the library if we haven't already loaded it
 		// even if the user overrides, we still need to validate the library
 		if libDir == "" {
@@ -357,7 +350,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 				return nil, err
 			}
 		}
-		gpuInfo.DependencyPath = []string{libDir}
+		gpuInfo.DependencyPath = libDir
 
 		if gfxOverride == "" {
 			// Only load supported list once
@@ -395,7 +388,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 
 		// Check for env var workarounds
 		if name == "1002:687f" { // Vega RX 56
-			gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, "HSA_ENABLE_SDMA=0")
+			gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, [2]string{"HSA_ENABLE_SDMA", "0"})
 		}
 
 		// The GPU has passed all the verification steps and is supported
@@ -523,27 +516,3 @@ func verifyKFDDriverAccess() error {
 	fd.Close()
 	return nil
 }
-
-func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) string {
-	ids := []string{}
-	for _, info := range gpuInfo {
-		if info.Library != "rocm" {
-			continue
-		}
-		// If the devices requires a numeric ID, for filtering purposes, we use the unfiltered ID number
-		if _, err := strconv.Atoi(info.ID); err == nil {
-			ids = append(ids, fmt.Sprintf("%d", info.filterID))
-		} else {
-			ids = append(ids, info.ID)
-		}
-	}
-	if len(ids) == 0 {
-		return ""
-	}
-
-	// There are 3 potential env vars to use to select GPUs.
-	// ROCR_VISIBLE_DEVICES supports UUID or numeric so is our preferred on linux
-	// GPU_DEVICE_ORDINAL supports numeric IDs only
-	// HIP_VISIBLE_DEVICES supports numeric IDs only
-	return "ROCR_VISIBLE_DEVICES=" + strings.Join(ids, ",")
-}

discover/amd_windows.go

@@ -5,6 +5,7 @@ import (
 	"errors"
 	"fmt"
 	"log/slog"
+	"os"
 	"path/filepath"
 	"slices"
 	"strconv"
@@ -42,14 +43,13 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 		slog.Debug("error looking up amd driver version", "error", err)
 	}
 
-	// Note: the HIP library automatically handles subsetting to any *_VISIBLE_DEVICES the user specified
+	// Note: the HIP library automatically handles subsetting to any HIP_VISIBLE_DEVICES the user specified
 	count := hl.HipGetDeviceCount()
 	if count == 0 {
 		err := fmt.Errorf("no compatible amdgpu devices detected")
 		slog.Info(err.Error())
 		return nil, err
 	}
-
 	libDir, err := AMDValidateLibDir()
 	if err != nil {
 		err = fmt.Errorf("unable to verify rocm library: %w", err)
@@ -111,8 +111,7 @@ func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
 				UnreliableFreeMemory: true,
 
 				ID:             strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
-				filterID:       i,
-				DependencyPath: []string{libDir},
+				DependencyPath: libDir,
 				MinimumMemory:  rocmMinimumMemory,
 				Name:           name,
 				Compute:        gfx,
@@ -163,7 +162,9 @@ func AMDValidateLibDir() (string, error) {
 	}
 
 	// Installer payload (if we're running from some other location)
-	rocmTargetDir := filepath.Join(LibOllamaPath, "rocm")
+	localAppData := os.Getenv("LOCALAPPDATA")
+	appDir := filepath.Join(localAppData, "Programs", "Ollama")
+	rocmTargetDir := filepath.Join(appDir, envconfig.LibRelativeToExe(), "lib", "ollama")
 	if rocmLibUsable(rocmTargetDir) {
 		slog.Debug("detected ollama installed ROCm at " + rocmTargetDir)
 		return rocmTargetDir, nil
@@ -181,7 +182,7 @@ func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
 	hl, err := NewHipLib()
 	if err != nil {
 		slog.Debug(err.Error())
-		return err
+		return nil
 	}
 	defer hl.Release()
 
@@ -200,27 +201,3 @@ func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
 	}
 	return nil
 }
-
-func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) string {
-	ids := []string{}
-	for _, info := range gpuInfo {
-		if info.Library != "rocm" {
-			continue
-		}
-		// If the devices requires a numeric ID, for filtering purposes, we use the unfiltered ID number
-		if _, err := strconv.Atoi(info.ID); err == nil {
-			ids = append(ids, fmt.Sprintf("%d", info.filterID))
-		} else {
-			ids = append(ids, info.ID)
-		}
-	}
-	if len(ids) == 0 {
-		return ""
-	}
-
-	// There are 3 potential env vars to use to select GPUs.
-	// ROCR_VISIBLE_DEVICES supports UUID or numeric but does not work on Windows
-	// HIP_VISIBLE_DEVICES supports numeric IDs only
-	// GPU_DEVICE_ORDINAL supports numeric IDs only
-	return "HIP_VISIBLE_DEVICES=" + strings.Join(ids, ",")
-}

discover/cpu_common.go

@@ -5,14 +5,27 @@ import (
 	"path/filepath"
 	"runtime"
 	"strings"
+
+	"golang.org/x/sys/cpu"
 )
 
+func GetCPUCapability() CPUCapability {
+	if cpu.X86.HasAVX2 {
+		return CPUCapabilityAVX2
+	}
+	if cpu.X86.HasAVX {
+		return CPUCapabilityAVX
+	}
+	// else LCD
+	return CPUCapabilityNone
+}
+
 func IsNUMA() bool {
 	if runtime.GOOS != "linux" {
 		// numa support in llama.cpp is linux only
 		return false
 	}
-	ids := map[string]any{}
+	ids := map[string]interface{}{}
 	packageIds, _ := filepath.Glob("/sys/devices/system/cpu/cpu*/topology/physical_package_id")
 	for _, packageId := range packageIds {
 		id, err := os.ReadFile(packageId)

discover/cuda_common.go

@@ -3,7 +3,6 @@
 package discover
 
 import (
-	"fmt"
 	"log/slog"
 	"os"
 	"regexp"
@@ -16,6 +15,19 @@ import (
 // Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
 var CudaTegra string = os.Getenv("JETSON_JETPACK")
 
+func cudaGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
+	ids := []string{}
+	for _, info := range gpuInfo {
+		if info.Library != "cuda" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("cudaGetVisibleDevicesEnv skipping over non-cuda device", "library", info.Library)
+			continue
+		}
+		ids = append(ids, info.ID)
+	}
+	return "CUDA_VISIBLE_DEVICES", strings.Join(ids, ",")
+}
+
 func cudaVariant(gpuInfo CudaGPUInfo) string {
 	if runtime.GOARCH == "arm64" && runtime.GOOS == "linux" {
 		if CudaTegra != "" {
@@ -45,13 +57,8 @@ func cudaVariant(gpuInfo CudaGPUInfo) string {
 		}
 	}
 
-	if gpuInfo.DriverMajor < 13 {
-		// The detected driver is older than 580 (Aug 2025)
-		// Warn if their CC is compatible with v13 and they should upgrade their driver to get better performance
-		if gpuInfo.computeMajor > 7 || (gpuInfo.computeMajor == 7 && gpuInfo.computeMinor >= 5) {
-			slog.Warn("old CUDA driver detected - please upgrade to a newer driver for best performance", "version", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor))
-		}
-		return "v12"
+	if gpuInfo.computeMajor < 6 || gpuInfo.DriverMajor < 12 || (gpuInfo.DriverMajor == 12 && gpuInfo.DriverMinor == 0) {
+		return "v11"
 	}
-	return "v13"
+	return "v12"
 }

discover/gpu.go

@@ -16,7 +16,6 @@ import (
 	"os"
 	"path/filepath"
 	"runtime"
-	"strconv"
 	"strings"
 	"sync"
 	"unsafe"
@@ -46,6 +45,7 @@ const (
 var (
 	gpuMutex      sync.Mutex
 	bootstrapped  bool
+	cpuCapability CPUCapability
 	cpus          []CPUInfo
 	cudaGPUs      []CudaGPUInfo
 	nvcudaLibPath string
@@ -64,13 +64,9 @@ var (
 )
 
 // With our current CUDA compile flags, older than 5.0 will not work properly
-// (string values used to allow ldflags overrides at build time)
-var (
-	CudaComputeMajorMin = "5"
-	CudaComputeMinorMin = "0"
-)
+var CudaComputeMin = [2]C.int{5, 0}
 
-var RocmComputeMajorMin = "9"
+var RocmComputeMin = 9
 
 // TODO find a better way to detect iGPU instead of minimum memory
 const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU
@@ -100,7 +96,15 @@ func initCudaHandles() *cudaHandles {
 
 	// Aligned with driver, we can't carry as payloads
 	nvcudaMgmtPatterns := NvcudaGlobs
-	cudartMgmtPatterns = append(cudartMgmtPatterns, filepath.Join(LibOllamaPath, "cuda_v*", CudartMgmtName))
+
+	if runtime.GOOS == "windows" {
+		localAppData := os.Getenv("LOCALAPPDATA")
+		cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", CudartMgmtName)}
+	}
+	libDir := LibraryDir()
+	if libDir != "" {
+		cudartMgmtPatterns = []string{filepath.Join(libDir, CudartMgmtName)}
+	}
 	cudartMgmtPatterns = append(cudartMgmtPatterns, CudartGlobs...)
 
 	if len(NvmlGlobs) > 0 {
@@ -215,23 +219,16 @@ func GetGPUInfo() GpuInfoList {
 
 	if !bootstrapped {
 		slog.Info("looking for compatible GPUs")
-		cudaComputeMajorMin, err := strconv.Atoi(CudaComputeMajorMin)
-		if err != nil {
-			slog.Error("invalid CudaComputeMajorMin setting", "value", CudaComputeMajorMin, "error", err)
-		}
-		cudaComputeMinorMin, err := strconv.Atoi(CudaComputeMinorMin)
-		if err != nil {
-			slog.Error("invalid CudaComputeMinorMin setting", "value", CudaComputeMinorMin, "error", err)
-		}
 		bootstrapErrors = []error{}
 		needRefresh = false
+		cpuCapability = GetCPUCapability()
 		var memInfo C.mem_info_t
 
 		mem, err := GetCPUMem()
 		if err != nil {
 			slog.Warn("error looking up system memory", "error", err)
 		}
-
+		depPath := LibraryDir()
 		details, err := GetCPUDetails()
 		if err != nil {
 			slog.Warn("failed to lookup CPU details", "error", err)
@@ -239,14 +236,26 @@ func GetGPUInfo() GpuInfoList {
 		cpus = []CPUInfo{
 			{
 				GpuInfo: GpuInfo{
-					memInfo: mem,
-					Library: "cpu",
-					ID:      "0",
+					memInfo:        mem,
+					Library:        "cpu",
+					Variant:        cpuCapability.String(),
+					ID:             "0",
+					DependencyPath: depPath,
 				},
 				CPUs: details,
 			},
 		}
 
+		// Fallback to CPU mode if we're lacking required vector extensions on x86
+		if cpuCapability < GPURunnerCPUCapability && runtime.GOARCH == "amd64" {
+			err := fmt.Errorf("CPU does not have minimum vector extensions, GPU inference disabled.  Required:%s  Detected:%s", GPURunnerCPUCapability, cpuCapability)
+			slog.Warn(err.Error())
+			bootstrapErrors = append(bootstrapErrors, err)
+			bootstrapped = true
+			// No need to do any GPU discovery, since we can't run on them
+			return GpuInfoList{cpus[0].GpuInfo}
+		}
+
 		// Load ALL libraries
 		cHandles = initCudaHandles()
 
@@ -263,8 +272,6 @@ func GetGPUInfo() GpuInfoList {
 				var driverMinor int
 				if cHandles.cudart != nil {
 					C.cudart_bootstrap(*cHandles.cudart, C.int(i), &memInfo)
-					driverMajor = int(cHandles.cudart.driver_major)
-					driverMinor = int(cHandles.cudart.driver_minor)
 				} else {
 					C.nvcuda_bootstrap(*cHandles.nvcuda, C.int(i), &memInfo)
 					driverMajor = int(cHandles.nvcuda.driver_major)
@@ -285,19 +292,19 @@ func GetGPUInfo() GpuInfoList {
 				gpuInfo.DriverMajor = driverMajor
 				gpuInfo.DriverMinor = driverMinor
 				variant := cudaVariant(gpuInfo)
-
-				// Start with our bundled libraries
-				if variant != "" {
-					variantPath := filepath.Join(LibOllamaPath, "cuda_"+variant)
-					if _, err := os.Stat(variantPath); err == nil {
-						// Put the variant directory first in the search path to avoid runtime linking to the wrong library
-						gpuInfo.DependencyPath = append([]string{variantPath}, gpuInfo.DependencyPath...)
+				if depPath != "" {
+					gpuInfo.DependencyPath = depPath
+					// Check for variant specific directory
+					if variant != "" {
+						if _, err := os.Stat(filepath.Join(depPath, "cuda_"+variant)); err == nil {
+							gpuInfo.DependencyPath = filepath.Join(depPath, "cuda_"+variant)
+						}
 					}
 				}
 				gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
 				gpuInfo.Variant = variant
 
-				if int(memInfo.major) < cudaComputeMajorMin || (int(memInfo.major) == cudaComputeMajorMin && int(memInfo.minor) < cudaComputeMinorMin) {
+				if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
 					unsupportedGPUs = append(unsupportedGPUs,
 						UnsupportedGPUInfo{
 							GpuInfo: gpuInfo.GpuInfo,
@@ -309,9 +316,7 @@ func GetGPUInfo() GpuInfoList {
 				// query the management library as well so we can record any skew between the two
 				// which represents overhead on the GPU we must set aside on subsequent updates
 				if cHandles.nvml != nil {
-					uuid := C.CString(gpuInfo.ID)
-					defer C.free(unsafe.Pointer(uuid))
-					C.nvml_get_free(*cHandles.nvml, uuid, &memInfo.free, &memInfo.total, &memInfo.used)
+					C.nvml_get_free(*cHandles.nvml, C.int(gpuInfo.index), &memInfo.free, &memInfo.total, &memInfo.used)
 					if memInfo.err != nil {
 						slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
 						C.free(unsafe.Pointer(memInfo.err))
@@ -363,7 +368,7 @@ func GetGPUInfo() GpuInfoList {
 						gpuInfo.FreeMemory = uint64(memInfo.free)
 						gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
 						gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
-						gpuInfo.DependencyPath = []string{LibOllamaPath}
+						gpuInfo.DependencyPath = depPath
 						oneapiGPUs = append(oneapiGPUs, gpuInfo)
 					}
 				}
@@ -371,15 +376,6 @@ func GetGPUInfo() GpuInfoList {
 		}
 
 		rocmGPUs, err = AMDGetGPUInfo()
-
-		// The ID field is used in context of the filtered set of GPUS
-		// so we have to replace any of these numeric IDs with their
-		// placement in this set of GPUs
-		for i := range rocmGPUs {
-			if _, err := strconv.Atoi(rocmGPUs[i].ID); err == nil {
-				rocmGPUs[i].ID = strconv.Itoa(i)
-			}
-		}
 		if err != nil {
 			bootstrapErrors = append(bootstrapErrors, err)
 		}
@@ -387,8 +383,6 @@ func GetGPUInfo() GpuInfoList {
 		if len(cudaGPUs) == 0 && len(rocmGPUs) == 0 && len(oneapiGPUs) == 0 {
 			slog.Info("no compatible GPUs were discovered")
 		}
-
-		// TODO verify we have runners for the discovered GPUs, filter out any that aren't supported with good error messages
 	}
 
 	// For detected GPUs, load library if not loaded
@@ -423,9 +417,7 @@ func GetGPUInfo() GpuInfoList {
 		}
 		for i, gpu := range cudaGPUs {
 			if cHandles.nvml != nil {
-				uuid := C.CString(gpu.ID)
-				defer C.free(unsafe.Pointer(uuid))
-				C.nvml_get_free(*cHandles.nvml, uuid, &memInfo.free, &memInfo.total, &memInfo.used)
+				C.nvml_get_free(*cHandles.nvml, C.int(gpu.index), &memInfo.free, &memInfo.total, &memInfo.used)
 			} else if cHandles.cudart != nil {
 				C.cudart_bootstrap(*cHandles.cudart, C.int(gpu.index), &memInfo)
 			} else if cHandles.nvcuda != nil {
@@ -508,33 +500,34 @@ func GetGPUInfo() GpuInfoList {
 
 func FindGPULibs(baseLibName string, defaultPatterns []string) []string {
 	// Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them
+	var ldPaths []string
 	gpuLibPaths := []string{}
 	slog.Debug("Searching for GPU library", "name", baseLibName)
 
-	// search our bundled libraries first
-	patterns := []string{filepath.Join(LibOllamaPath, baseLibName)}
+	// Start with our bundled libraries
+	patterns := []string{filepath.Join(LibraryDir(), baseLibName)}
 
-	var ldPaths []string
 	switch runtime.GOOS {
 	case "windows":
-		ldPaths = strings.Split(os.Getenv("PATH"), string(os.PathListSeparator))
+		ldPaths = strings.Split(os.Getenv("PATH"), ";")
 	case "linux":
-		ldPaths = strings.Split(os.Getenv("LD_LIBRARY_PATH"), string(os.PathListSeparator))
+		ldPaths = strings.Split(os.Getenv("LD_LIBRARY_PATH"), ":")
+	default:
+		return gpuLibPaths
 	}
 
-	// then search the system's LD_LIBRARY_PATH
-	for _, p := range ldPaths {
-		p, err := filepath.Abs(p)
+	// Then with whatever we find in the PATH/LD_LIBRARY_PATH
+	for _, ldPath := range ldPaths {
+		d, err := filepath.Abs(ldPath)
 		if err != nil {
 			continue
 		}
-		patterns = append(patterns, filepath.Join(p, baseLibName))
+		patterns = append(patterns, filepath.Join(d, baseLibName))
 	}
-
-	// finally, search the default patterns provided by the caller
 	patterns = append(patterns, defaultPatterns...)
 	slog.Debug("gpu library search", "globs", patterns)
 	for _, pattern := range patterns {
+
 		// Nvidia PhysX known to return bogus results
 		if strings.Contains(pattern, "PhysX") {
 			slog.Debug("skipping PhysX cuda library path", "path", pattern)
@@ -681,7 +674,7 @@ func loadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string, e
 }
 
 func getVerboseState() C.uint16_t {
-	if envconfig.LogLevel() < slog.LevelInfo {
+	if envconfig.Debug() {
 		return C.uint16_t(1)
 	}
 	return C.uint16_t(0)
@@ -689,16 +682,51 @@ func getVerboseState() C.uint16_t {
 
 // Given the list of GPUs this instantiation is targeted for,
 // figure out the visible devices environment variable
-func (l GpuInfoList) GetVisibleDevicesEnv() []string {
+//
+// If different libraries are detected, the first one is what we use
+func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
 	if len(l) == 0 {
-		return nil
+		return "", ""
 	}
-	vd := []string{}
-	// Only filter the AMD GPUs at this level, let all NVIDIA devices through
-	if tmp := rocmGetVisibleDevicesEnv(l); tmp != "" {
-		vd = append(vd, tmp)
+	switch l[0].Library {
+	case "cuda":
+		return cudaGetVisibleDevicesEnv(l)
+	case "rocm":
+		return rocmGetVisibleDevicesEnv(l)
+	case "oneapi":
+		return oneapiGetVisibleDevicesEnv(l)
+	default:
+		slog.Debug("no filter required for library " + l[0].Library)
+		return "", ""
 	}
-	return vd
+}
+
+func LibraryDir() string {
+	// On Windows/linux we bundle the dependencies at the same level as the executable
+	appExe, err := os.Executable()
+	if err != nil {
+		slog.Warn("failed to lookup executable path", "error", err)
+	}
+	cwd, err := os.Getwd()
+	if err != nil {
+		slog.Warn("failed to lookup working directory", "error", err)
+	}
+	// Scan for any of our dependeices, and pick first match
+	for _, root := range []string{filepath.Dir(appExe), filepath.Join(filepath.Dir(appExe), envconfig.LibRelativeToExe()), cwd} {
+		libDep := filepath.Join("lib", "ollama")
+		if _, err := os.Stat(filepath.Join(root, libDep)); err == nil {
+			return filepath.Join(root, libDep)
+		}
+		// Developer mode, local build
+		if _, err := os.Stat(filepath.Join(root, runtime.GOOS+"-"+runtime.GOARCH, libDep)); err == nil {
+			return filepath.Join(root, runtime.GOOS+"-"+runtime.GOARCH, libDep)
+		}
+		if _, err := os.Stat(filepath.Join(root, "dist", runtime.GOOS+"-"+runtime.GOARCH, libDep)); err == nil {
+			return filepath.Join(root, "dist", runtime.GOOS+"-"+runtime.GOARCH, libDep)
+		}
+	}
+	slog.Warn("unable to locate gpu dependency libraries")
+	return ""
 }
 
 func GetSystemInfo() SystemInfo {

discover/gpu_darwin.go

@@ -27,6 +27,7 @@ func GetGPUInfo() GpuInfoList {
 		return []GpuInfo{
 			{
 				Library: "cpu",
+				Variant: GetCPUCapability().String(),
 				memInfo: mem,
 			},
 		}
@@ -49,6 +50,7 @@ func GetCPUInfo() GpuInfoList {
 	return []GpuInfo{
 		{
 			Library: "cpu",
+			Variant: GetCPUCapability().String(),
 			memInfo: mem,
 		},
 	}
@@ -62,9 +64,9 @@ func GetCPUMem() (memInfo, error) {
 	}, nil
 }
 
-func (l GpuInfoList) GetVisibleDevicesEnv() []string {
+func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
 	// No-op on darwin
-	return nil
+	return "", ""
 }
 
 func GetSystemInfo() SystemInfo {

discover/gpu_info.h

@@ -27,14 +27,12 @@
 
 #endif
 
-#ifndef LOG
 #define LOG(verbose, ...) \
   do { \
     if (verbose) { \
       fprintf(stderr, __VA_ARGS__); \
     } \
   } while (0)
-#endif
 
 #ifdef __cplusplus
 extern "C" {

discover/gpu_info_cudart.c

@@ -1,7 +1,6 @@
 #ifndef __APPLE__  // TODO - maybe consider nvidia support on intel macs?
 
 #include <string.h>
-#include <inttypes.h>
 #include "gpu_info_cudart.h"
 
 void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
@@ -59,7 +58,7 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
     LOG(resp->ch.verbose, "cudaSetDevice err: %d\n", ret);
     UNLOAD_LIBRARY(resp->ch.handle);
     resp->ch.handle = NULL;
-    if (ret == CUDART_ERROR_INSUFFICIENT_DRIVER) {
+    if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
       resp->err = strdup("your nvidia driver is too old or missing.  If you have a CUDA GPU please upgrade to run ollama");
       return;
     }
@@ -69,15 +68,18 @@ void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
   }
 
   int version = 0;
+  cudartDriverVersion_t driverVersion;
+  driverVersion.major = 0;
+  driverVersion.minor = 0;
 
   // Report driver version if we're in verbose mode, ignore errors
   ret = (*resp->ch.cudaDriverGetVersion)(&version);
   if (ret != CUDART_SUCCESS) {
     LOG(resp->ch.verbose, "cudaDriverGetVersion failed: %d\n", ret);
   } else {
-    resp->ch.driver_major = version / 1000;
-    resp->ch.driver_minor = (version - (resp->ch.driver_major * 1000)) / 10;
-    LOG(resp->ch.verbose, "CUDA driver version: %d-%d\n", resp->ch.driver_major, resp->ch.driver_minor);
+    driverVersion.major = version / 1000;
+    driverVersion.minor = (version - (driverVersion.major * 1000)) / 10;
+    LOG(resp->ch.verbose, "CUDA driver version: %d-%d\n", driverVersion.major, driverVersion.minor);
   }
 
   ret = (*resp->ch.cudaGetDeviceCount)(&resp->num_devices);
@@ -166,9 +168,9 @@ void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
   resp->free = memInfo.free;
   resp->used = memInfo.used;
 
-  LOG(h.verbose, "[%s] CUDA totalMem %" PRId64 "\n", resp->gpu_id, resp->total);
-  LOG(h.verbose, "[%s] CUDA freeMem %" PRId64 "\n", resp->gpu_id, resp->free);
-  LOG(h.verbose, "[%s] CUDA usedMem %" PRId64 "\n", resp->gpu_id, resp->used);
+  LOG(h.verbose, "[%s] CUDA totalMem %lu\n", resp->gpu_id, resp->total);
+  LOG(h.verbose, "[%s] CUDA freeMem %lu\n", resp->gpu_id, resp->free);
+  LOG(h.verbose, "[%s] CUDA usedMem %lu\n", resp->gpu_id, resp->used);
   LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
 }
 
@@ -178,4 +180,4 @@ void cudart_release(cudart_handle_t h) {
   h.handle = NULL;
 }
 
-#endif  // __APPLE__
+#endif  // __APPLE__

discover/gpu_info_cudart.h

@@ -29,6 +29,11 @@ typedef struct cudartMemory_st {
   size_t used;
 } cudartMemory_t;
 
+typedef struct cudartDriverVersion {
+  int major;
+  int minor;
+} cudartDriverVersion_t;
+
 typedef struct cudaUUID {
     unsigned char bytes[16];
 } cudaUUID_t;
@@ -118,8 +123,6 @@ typedef struct cudaDeviceProp {
 typedef struct cudart_handle {
   void *handle;
   uint16_t verbose;
-  int driver_major;
-  int driver_minor;
   cudartReturn_t (*cudaSetDevice)(int device);
   cudartReturn_t (*cudaDeviceSynchronize)(void);
   cudartReturn_t (*cudaDeviceReset)(void);

discover/gpu_info_nvcuda.c

@@ -1,11 +1,9 @@
 #ifndef __APPLE__  // TODO - maybe consider nvidia support on intel macs?
 
 #include <string.h>
-#include <inttypes.h>
 #include "gpu_info_nvcuda.h"
 
 void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
-  LOG(resp->ch.verbose, "initializing %s\n", nvcuda_lib_path);
   CUresult ret;
   resp->err = NULL;
   resp->num_devices = 0;
@@ -59,10 +57,8 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
       resp->cudaErr = -1;
       return;
     }
-    LOG(resp->ch.verbose, "dlsym: %s - %p\n", l[i].s, *l[i].p);
   }
 
-  LOG(resp->ch.verbose, "calling cuInit\n");
   ret = (*resp->ch.cuInit)(0);
   if (ret != CUDA_SUCCESS) {
     LOG(resp->ch.verbose, "cuInit err: %d\n", ret);
@@ -79,18 +75,15 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
   resp->ch.driver_minor = 0;
 
   // Report driver version if we're in verbose mode, ignore errors
-  LOG(resp->ch.verbose, "calling cuDriverGetVersion\n");
   ret = (*resp->ch.cuDriverGetVersion)(&version);
   if (ret != CUDA_SUCCESS) {
     LOG(resp->ch.verbose, "cuDriverGetVersion failed: %d\n", ret);
   } else {
-    LOG(resp->ch.verbose, "raw version 0x%x\n", version);
     resp->ch.driver_major = version / 1000;
     resp->ch.driver_minor = (version - (resp->ch.driver_major * 1000)) / 10;
     LOG(resp->ch.verbose, "CUDA driver version: %d.%d\n", resp->ch.driver_major, resp->ch.driver_minor);
   }
 
-  LOG(resp->ch.verbose, "calling cuDeviceGetCount\n");
   ret = (*resp->ch.cuDeviceGetCount)(&resp->num_devices);
   if (ret != CUDA_SUCCESS) {
     LOG(resp->ch.verbose, "cuDeviceGetCount err: %d\n", ret);
@@ -101,7 +94,6 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
     resp->cudaErr = ret;
     return;
   }
-  LOG(resp->ch.verbose, "device count %d\n", resp->num_devices);
 }
 
 const int buflen = 256;
@@ -194,8 +186,8 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
   resp->total = memInfo.total;
   resp->free = memInfo.free;
 
-  LOG(h.verbose, "[%s] CUDA totalMem %" PRId64 "mb\n", resp->gpu_id, resp->total / 1024 / 1024);
-  LOG(h.verbose, "[%s] CUDA freeMem %" PRId64 "mb\n", resp->gpu_id, resp->free / 1024 / 1024);
+  LOG(h.verbose, "[%s] CUDA totalMem %lu mb\n", resp->gpu_id, resp->total / 1024 / 1024);
+  LOG(h.verbose, "[%s] CUDA freeMem %lu mb\n", resp->gpu_id, resp->free / 1024 / 1024);
   LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
 
   
@@ -248,4 +240,4 @@ void nvcuda_release(nvcuda_handle_t h) {
   h.handle = NULL;
 }
 
-#endif  // __APPLE__
+#endif  // __APPLE__

discover/gpu_info_nvml.c

@@ -17,7 +17,7 @@ void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
   } l[] = {
       {"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
       {"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
-      {"nvmlDeviceGetHandleByUUID", (void *)&resp->ch.nvmlDeviceGetHandleByUUID},
+      {"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.nvmlDeviceGetHandleByIndex},
       {"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
       {NULL, NULL},
   };
@@ -67,20 +67,20 @@ void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
 }
 
 
-void nvml_get_free(nvml_handle_t h, char *uuid, uint64_t *free, uint64_t *total, uint64_t *used) {
+void nvml_get_free(nvml_handle_t h, int device_id, uint64_t *free, uint64_t *total, uint64_t *used) {
     nvmlDevice_t device;
     nvmlMemory_t memInfo = {0};
     nvmlReturn_t ret;
-    ret = (*h.nvmlDeviceGetHandleByUUID)((const char *)(uuid), &device);
+    ret = (*h.nvmlDeviceGetHandleByIndex)(device_id, &device);
     if (ret != NVML_SUCCESS) {
-        LOG(1, "unable to get device handle %s: %d", uuid, ret);
+        LOG(1, "unable to get device handle %d: %d", device_id, ret);
         *free = 0;
         return;
     }
 
     ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
     if (ret != NVML_SUCCESS) {
-        LOG(1, "device memory info lookup failure %s: %d", uuid, ret);
+        LOG(1, "device memory info lookup failure %d: %d", device_id, ret);
         *free = 0;
         return;
     }

discover/gpu_info_nvml.h

@@ -25,7 +25,7 @@ typedef struct nvml_handle {
   uint16_t verbose;
   nvmlReturn_t (*nvmlInit_v2)(void);
   nvmlReturn_t (*nvmlShutdown)(void);
-  nvmlReturn_t (*nvmlDeviceGetHandleByUUID)(const char *, nvmlDevice_t *);
+  nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t *);
   nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
 } nvml_handle_t;
 
@@ -41,7 +41,7 @@ typedef struct nvml_compute_capability {
 } nvml_compute_capability_t;
 
 void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp);
-void nvml_get_free(nvml_handle_t ch, char *uuid, uint64_t *free, uint64_t *total, uint64_t *used);
+void nvml_get_free(nvml_handle_t ch,  int device_id, uint64_t *free, uint64_t *total, uint64_t *used);
 void nvml_release(nvml_handle_t ch);
 
 #endif  // __GPU_INFO_NVML_H__

discover/gpu_linux.go

@@ -3,11 +3,9 @@ package discover
 import (
 	"bufio"
 	"fmt"
-	"io"
 	"os"
 	"reflect"
 	"regexp"
-	"sort"
 	"strings"
 
 	"github.com/ollama/ollama/format"
@@ -111,11 +109,6 @@ func GetCPUDetails() ([]CPU, error) {
 	if err != nil {
 		return nil, err
 	}
-	defer file.Close()
-	return linuxCPUDetails(file)
-}
-
-func linuxCPUDetails(file io.Reader) ([]CPU, error) {
 	reColumns := regexp.MustCompile("\t+: ")
 	scanner := bufio.NewScanner(file)
 	cpuInfos := []linuxCpuInfo{}
@@ -138,9 +131,6 @@ func linuxCPUDetails(file io.Reader) ([]CPU, error) {
 			cpu = &linuxCpuInfo{}
 		}
 	}
-	if cpu.ID != "" {
-		cpuInfos = append(cpuInfos, *cpu)
-	}
 
 	// Process the sockets/cores/threads
 	socketByID := map[string]*CPU{}
@@ -169,11 +159,13 @@ func linuxCPUDetails(file io.Reader) ([]CPU, error) {
 	for id, s := range socketByID {
 		s.CoreCount = len(coreBySocket[id])
 		s.ThreadCount = 0
+		for _, tc := range threadsByCoreBySocket[id] {
+			s.ThreadCount += tc
+		}
 
 		// This only works if HT is enabled, consider a more reliable model, maybe cache size comparisons?
 		efficiencyCoreCount := 0
 		for _, threads := range threadsByCoreBySocket[id] {
-			s.ThreadCount += threads
 			if threads == 1 {
 				efficiencyCoreCount++
 			}
@@ -185,14 +177,10 @@ func linuxCPUDetails(file io.Reader) ([]CPU, error) {
 			s.EfficiencyCoreCount = efficiencyCoreCount
 		}
 	}
-	keys := make([]string, 0, len(socketByID))
-	result := make([]CPU, 0, len(socketByID))
-	for k := range socketByID {
-		keys = append(keys, k)
-	}
-	sort.Strings(keys)
-	for _, k := range keys {
-		result = append(result, *socketByID[k])
+
+	result := []CPU{}
+	for _, c := range socketByID {
+		result = append(result, *c)
 	}
 	return result, nil
 }