punch the linter again

.dockerignore

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

.gitattributes

@@ -1,24 +1 @@
-llama/**/*.cpp linguist-vendored
-llama/**/*.hpp linguist-vendored
-llama/**/*.h linguist-vendored
-llama/**/*.c linguist-vendored
-llama/**/*.cu linguist-vendored
-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
+llm/ext_server/* linguist-vendored

.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/release.yaml

@@ -5,62 +5,23 @@ on:
     tags:
       - 'v*'
 
-env:
-  CGO_CFLAGS: '-O3'
-  CGO_CXXFLAGS: '-O3'
-
 jobs:
-  setup-environment:
-    runs-on: ubuntu-latest
+  # Full build of the Mac assets
+  build-darwin:
+    runs-on: macos-12
     environment: release
-    outputs:
-      GOFLAGS: ${{ steps.goflags.outputs.GOFLAGS }}
     steps:
       - uses: actions/checkout@v4
-      - name: Set environment
-        id: goflags
+      - name: Set Version
+        shell: bash
         run: |
-          echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${GITHUB_REF_NAME#v}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_OUTPUT
-
-  darwin-build:
-    runs-on: macos-13
-    environment: release
-    needs: setup-environment
-    strategy:
-      matrix:
-        os: [darwin]
-        arch: [amd64, arm64]
-    env:
-      GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
-    steps:
-      - uses: actions/checkout@v4
-      - uses: actions/setup-go@v5
-        with:
-          go-version-file: go.mod
-      - run: |
-          go build -o dist/ .
+          echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+          echo "RELEASE_VERSION=$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)" >> $GITHUB_ENV
+      - name: key
         env:
-          GOOS: ${{ matrix.os }}
-          GOARCH: ${{ matrix.arch }}
-          CGO_ENABLED: 1
-          CGO_CPPFLAGS: '-mmacosx-version-min=11.3'
-      - if: matrix.arch == 'amd64'
+          MACOS_SIGNING_KEY: ${{ secrets.MACOS_SIGNING_KEY }}
+          MACOS_SIGNING_KEY_PASSWORD: ${{ secrets.MACOS_SIGNING_KEY_PASSWORD }}
         run: |
-          cmake --preset CPU -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_PROCESSOR=x86_64 -DCMAKE_OSX_ARCHITECTURES=x86_64
-          cmake --build --parallel --preset CPU
-          cmake --install build --component CPU --strip --parallel 8
-      - uses: actions/upload-artifact@v4
-        with:
-          name: build-${{ matrix.os }}-${{ matrix.arch }}
-          path: dist/*
-
-  darwin-sign:
-    runs-on: macos-13
-    environment: release
-    needs: darwin-build
-    steps:
-      - uses: actions/checkout@v4
-      - run: |
           echo $MACOS_SIGNING_KEY | base64 --decode > certificate.p12
           security create-keychain -p password build.keychain
           security default-keychain -s build.keychain
@@ -68,409 +29,454 @@ jobs:
           security import certificate.p12 -k build.keychain -P $MACOS_SIGNING_KEY_PASSWORD -T /usr/bin/codesign
           security set-key-partition-list -S apple-tool:,apple:,codesign: -s -k password build.keychain
           security set-keychain-settings -lut 3600 build.keychain
-        env:
-          MACOS_SIGNING_KEY: ${{ secrets.MACOS_SIGNING_KEY }}
-          MACOS_SIGNING_KEY_PASSWORD: ${{ secrets.MACOS_SIGNING_KEY_PASSWORD }}
-      - uses: actions/download-artifact@v4
+      - uses: actions/setup-go@v5
         with:
-          name: build-darwin-amd64
-          path: dist/darwin-amd64
-      - uses: actions/download-artifact@v4
-        with:
-          name: build-darwin-arm64
-          path: dist/darwin-arm64
-      - run: |
-          export VERSION=${GITHUB_REF_NAME#v}
-          ./scripts/build_darwin.sh sign macapp
+          go-version-file: go.mod
+          cache: true
+      - name: Build Darwin
         env:
           APPLE_IDENTITY: ${{ secrets.APPLE_IDENTITY }}
           APPLE_PASSWORD: ${{ secrets.APPLE_PASSWORD }}
           APPLE_TEAM_ID: ${{ vars.APPLE_TEAM_ID }}
           APPLE_ID: ${{ vars.APPLE_ID }}
-          SDKROOT: /Applications/Xcode_14.1.0.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
-          DEVELOPER_DIR: /Applications/Xcode_14.1.0.app/Contents/Developer
+          SDKROOT: /Applications/Xcode_13.4.1.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
+          DEVELOPER_DIR: /Applications/Xcode_13.4.1.app/Contents/Developer
+        run: |
+          ./scripts/build_darwin.sh
+
       - uses: actions/upload-artifact@v4
         with:
           name: dist-darwin
           path: |
-            dist/Ollama-darwin.zip
-            dist/ollama-darwin.tgz
+            dist/*arwin*
+            !dist/*-cov
 
-  windows-depends:
-    strategy:
-      matrix:
-        os: [windows]
-        arch: [amd64]
-        preset: ['CPU']
-        include:
-          - os: windows
-            arch: amd64
-            preset: 'CUDA 11'
-            install: https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe
-            cuda-version: '11.3'
-          - os: windows
-            arch: amd64
-            preset: 'CUDA 12'
-            install: https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_571.96_windows.exe
-            cuda-version: '12.8'
-          - os: windows
-            arch: amd64
-            preset: 'ROCm 6'
-            install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
-            rocm-version: '6.2'
-    runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
+  # Windows builds take a long time to both install the dependencies and build, so parallelize
+  # CPU generation step
+  generate-windows-cpu:
     environment: release
+    runs-on: windows
     env:
-      GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
+      KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
     steps:
-      - name: Install system dependencies
-        run: |
-          choco install -y --no-progress ccache ninja
-          ccache -o cache_dir=${{ github.workspace }}\.ccache
-      - if: startsWith(matrix.preset, 'CUDA ') || startsWith(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: startsWith(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"
-            $subpackages = @("cudart", "nvcc", "cublas", "cublas_dev") | Foreach-Object {"${_}_${{ 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: startsWith(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
-      - if: matrix.preset == 'CPU'
-        run: |
-          echo "CC=clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
-          echo "CXX=clang++.exe" | 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: ${{ matrix.install }}
       - uses: actions/checkout@v4
-      - uses: actions/cache@v4
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - uses: 'google-github-actions/auth@v2'
         with:
-          path: ${{ github.workspace }}\.ccache
-          key: ccache-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}
-      - name: Build target "${{ matrix.preset }}"
-        run: |
-          Import-Module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
-          Enter-VsDevShell -VsInstallPath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
-          cmake --preset "${{ matrix.preset }}"
-          cmake --build --parallel --preset "${{ matrix.preset }}"
-          cmake --install build --component "${{ startsWith(matrix.preset, 'CUDA ') && 'CUDA' || startsWith(matrix.preset, 'ROCm ') && 'HIP' || 'CPU' }}" --strip --parallel 8
-        env:
-          CMAKE_GENERATOR: Ninja
-      - uses: actions/upload-artifact@v4
-        with:
-          name: depends-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.preset }}
-          path: dist\*
-
-  windows-build:
-    strategy:
-      matrix:
-        os: [windows]
-        arch: [amd64, arm64]
-    runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
-    environment: release
-    needs: [setup-environment]
-    env:
-      GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
-    steps:
-      - name: Install AMD64 system dependencies
-        if: matrix.arch == 'amd64'
+          project_id: 'ollama'
+          credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
+      - run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
+      - name: install Windows SDK 8.1 to get signtool
         run: |
           $ErrorActionPreference = "Stop"
-          Start-Process "C:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang") -NoNewWindow -Wait
-          echo "C:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-          echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-      - name: Install ARM64 system dependencies
-        if: matrix.arch == 'arm64'
+          write-host "downloading SDK"
+          Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
+          Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
+          write-host "Win SDK 8.1 installed"
+          gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
+      - name: install signing plugin
         run: |
           $ErrorActionPreference = "Stop"
-          Set-ExecutionPolicy Bypass -Scope Process -Force
-          [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072
-          iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
-          echo "C:\ProgramData\chocolatey\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-
-          choco install -y --no-progress git gzip
-          echo "C:\Program Files\Git\cmd" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-
-          Invoke-WebRequest -Uri "https://github.com/mstorsjo/llvm-mingw/releases/download/20240619/llvm-mingw-20240619-ucrt-aarch64.zip" -OutFile "${{ runner.temp }}\llvm-mingw-ucrt-aarch64.zip"
-          Expand-Archive -Path ${{ runner.temp }}\llvm-mingw-ucrt-aarch64.zip -DestinationPath "C:\Program Files\"
-          $installPath=(Resolve-Path -Path "C:\Program Files\llvm-mingw-*-ucrt-aarch64").path
-          echo $installPath\bin | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-      - uses: actions/checkout@v4
+          write-host "downloading plugin"
+          Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
+          Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
+          write-host "Installing plugin"
+          & "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
+          write-host "plugin installed"
       - uses: actions/setup-go@v5
         with:
           go-version-file: go.mod
+          cache: true
+      - run: go get ./...
       - run: |
-          go build -o dist/${{ matrix.os }}-${{ matrix.arch }}/ .
-      - if: matrix.arch == 'arm64'
-        run: |
-          Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vc_redist.arm64.exe" -OutFile "dist\windows-arm64\vc_redist.arm64.exe"
-      - run: |
-          $env:VERSION='${{ github.ref_name }}' -Replace "v(.*)", '$1'
-          & .\scripts\build_windows.ps1 buildApp
-        env:
-          VCToolsRedistDir: stub
+          $gopath=(get-command go).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$env:PATH"
+          go generate -x ./...
+        name: go generate
       - uses: actions/upload-artifact@v4
         with:
-          name: build-${{ matrix.os }}-${{ matrix.arch }}
+          name: generate-windows-cpu
           path: |
-            dist\${{ matrix.os }}-${{ matrix.arch }}\*.exe
-            dist\${{ matrix.os }}-${{ matrix.arch }}-app.exe
+            llm/build/**/bin/*
+            llm/build/**/*.a
+            dist/windows-amd64/**
 
-  windows-sign:
-    runs-on: windows-2022
+  # ROCm generation step
+  generate-windows-rocm:
     environment: release
-    needs: [windows-depends, windows-build]
+    runs-on: windows
+    env:
+      KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
     steps:
       - uses: actions/checkout@v4
-      - uses: google-github-actions/auth@v2
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - uses: 'google-github-actions/auth@v2'
         with:
-          project_id: ollama
-          credentials_json: ${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}
-      - run: |
+          project_id: 'ollama'
+          credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
+      - run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
+      - name: install Windows SDK 8.1 to get signtool
+        run: |
           $ErrorActionPreference = "Stop"
-          Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${{ runner.temp }}\sdksetup.exe"
-          Start-Process "${{ runner.temp }}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
-
-          Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${{ runner.temp }}\plugin.zip"
-          Expand-Archive -Path "${{ runner.temp }}\plugin.zip" -DestinationPath "${{ runner.temp }}\plugin\"
-          & "${{ runner.temp }}\plugin\*\kmscng.msi" /quiet
-
-          echo "${{ vars.OLLAMA_CERT }}" >ollama_inc.crt
-      - uses: actions/download-artifact@v4
+          write-host "downloading SDK"
+          Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
+          Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
+          write-host "Win SDK 8.1 installed"
+          gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
+      - name: install signing plugin
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading plugin"
+          Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
+          Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
+          write-host "Installing plugin"
+          & "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
+          write-host "plugin installed"
+      - uses: actions/setup-go@v5
         with:
-          pattern: build-windows-*
-          path: dist\
-          merge-multiple: true
-      - uses: actions/download-artifact@v4
-        with:
-          pattern: depends-windows-amd64-*
-          path: dist\windows-amd64\
-          merge-multiple: true
+          go-version-file: go.mod
+          cache: true
+      - name: 'Install ROCm'
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading AMD HIP Installer"
+          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${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: |
-          & .\scripts\build_windows.ps1 gatherDependencies sign buildInstaller distZip
-        env:
-          KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
+          $gopath=(get-command go).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$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)
+          go generate -x ./...
+        name: go generate
+      - name: 'gather rocm dependencies'
+        run: |
+          $HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
+          md "dist\deps\bin\rocblas\library"
+          cp "${HIP_PATH}\bin\hipblas.dll" "dist\deps\bin\"
+          cp "${HIP_PATH}\bin\rocblas.dll" "dist\deps\bin\"
+          cp "${HIP_PATH}\bin\rocblas\library\*" "dist\deps\bin\rocblas\library\"
+      - uses: actions/upload-artifact@v4
+        with:
+          name: generate-windows-rocm
+          path: |
+            llm/build/**/bin/*
+            dist/windows-amd64/**
+      - uses: actions/upload-artifact@v4
+        with:
+          name: windows-rocm-deps
+          path: dist/deps/*
+
+  # CUDA generation step
+  generate-windows-cuda:
+    environment: release
+    runs-on: windows
+    env:
+      KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - uses: 'google-github-actions/auth@v2'
+        with:
+          project_id: 'ollama'
+          credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
+      - run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
+      - name: install Windows SDK 8.1 to get signtool
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading SDK"
+          Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
+          Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
+          write-host "Win SDK 8.1 installed"
+          gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
+      - name: install signing plugin
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading plugin"
+          Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
+          Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
+          write-host "Installing plugin"
+          & "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
+          write-host "plugin installed"
+      - 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: go generate
+        run: |
+          $gopath=(get-command go).source | split-path -parent
+          $cudabin=(get-command nvcc).source | split-path
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$cudabin;$env:PATH"
+          $env:OLLAMA_SKIP_CPU_GENERATE="1"
+          go generate -x ./...
+      - name: 'gather cuda dependencies'
+        run: |
+          $NVIDIA_DIR=(resolve-path 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\*\bin\')[0]
+          md "dist\deps"
+          cp "${NVIDIA_DIR}\cudart64_*.dll" "dist\deps\"
+          cp "${NVIDIA_DIR}\cublas64_*.dll" "dist\deps\"
+          cp "${NVIDIA_DIR}\cublasLt64_*.dll" "dist\deps\"
+      - uses: actions/upload-artifact@v4
+        with:
+          name: generate-windows-cuda
+          path: |
+            llm/build/**/bin/*
+            dist/windows-amd64/**
+      - uses: actions/upload-artifact@v4
+        with:
+          name: windows-cuda-deps
+          path: dist/deps/*
+
+  # Import the prior generation steps and build the final windows assets
+  build-windows:
+    environment: release
+    runs-on: windows
+    needs:
+      - generate-windows-cuda
+      - generate-windows-rocm
+      - generate-windows-cpu
+    env:
+      KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - uses: 'google-github-actions/auth@v2'
+        with:
+          project_id: 'ollama'
+          credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
+      - run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
+      - name: install Windows SDK 8.1 to get signtool
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading SDK"
+          Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
+          Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
+          write-host "Win SDK 8.1 installed"
+          gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
+      - name: install signing plugin
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading plugin"
+          Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
+          Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
+          write-host "Installing plugin"
+          & "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
+          write-host "plugin installed"
+      - name: remove unwanted mingw dll.a files
+        run: |
+          Get-ChildItem -Path "C:\mingw64" -Recurse -Filter "libpthread.dll.a" -File | Remove-Item -Force
+          Get-ChildItem -Path "C:\mingw64" -Recurse -Filter "libwinpthread.dll.a" -File | Remove-Item -Force
+          Get-ChildItem -Path "C:\mingw64" -Recurse -Filter "libstdc++.dll.a" -File | Remove-Item -Force
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+      - run: go get
+      - uses: actions/download-artifact@v4
+        with:
+          name: generate-windows-cpu
+      - uses: actions/download-artifact@v4
+        with:
+          name: generate-windows-cuda
+      - uses: actions/download-artifact@v4
+        with:
+          name: windows-cuda-deps
+      - uses: actions/download-artifact@v4
+        with:
+          name: windows-rocm-deps
+      - uses: actions/download-artifact@v4
+        with:
+          name: generate-windows-rocm
+      - run: dir llm/build
+      - run: |
+          $gopath=(get-command go).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$env:PATH"
+          $env:OLLAMA_SKIP_GENERATE="1"
+          & .\scripts\build_windows.ps1
       - uses: actions/upload-artifact@v4
         with:
           name: dist-windows
           path: |
-            dist\OllamaSetup.exe
-            dist\ollama-windows-*.zip
+            dist/OllamaSetup.exe
+            dist/ollama-windows-*.zip
 
-  linux-build:
-    strategy:
-      matrix:
-        include:
-          - os: linux
-            arch: amd64
-            target: archive
-          - os: linux
-            arch: amd64
-            target: rocm
-          - os: linux
-            arch: arm64
-            target: archive
-    runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
+  # Linux x86 assets built using the container based build
+  build-linux-amd64:
     environment: release
-    needs: setup-environment
-    env:
-      GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
-    steps:
-      - uses: actions/checkout@v4
-      - uses: docker/setup-buildx-action@v3
-      - uses: docker/build-push-action@v6
-        with:
-          context: .
-          platforms: ${{ matrix.os }}/${{ matrix.arch }}
-          target: ${{ matrix.target }}
-          build-args: |
-            GOFLAGS=${{ env.GOFLAGS }}
-            CGO_CFLAGS=${{ env.CGO_CFLAGS }}
-            CGO_CXXFLAGS=${{ env.CGO_CXXFLAGS }}
-          outputs: type=local,dest=dist/${{ matrix.os }}-${{ matrix.arch }}
-          cache-from: type=registry,ref=ollama/ollama:latest
-          cache-to: type=inline
-      - run: |
-          for COMPONENT in bin/* lib/ollama/*; do
-            case "$COMPONENT" in
-              bin/ollama)               echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/*.so)          echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/cuda_v11)      echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/cuda_v12)      echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}.tar.in ;;
-              lib/ollama/cuda_jetpack5) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack5.tar.in ;;
-              lib/ollama/cuda_jetpack6) echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-jetpack6.tar.in ;;
-              lib/ollama/rocm)          echo $COMPONENT >>ollama-${{ matrix.os }}-${{ matrix.arch }}-rocm.tar.in ;;
-            esac
-          done
-        working-directory: dist/${{ matrix.os }}-${{ matrix.arch }}
-      - run: |
-          for ARCHIVE in dist/${{ matrix.os }}-${{ matrix.arch }}/*.tar.in; do
-            tar c -C dist/${{ matrix.os }}-${{ matrix.arch }} -T $ARCHIVE --owner 0 --group 0 | pigz -9vc >$(basename ${ARCHIVE//.*/}.tgz);
-          done
-      - uses: actions/upload-artifact@v4
-        with:
-          name: dist-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.target }}
-          path: |
-            *.tgz
-
-  # Build each Docker variant (OS, arch, and flavor) separately. Using QEMU is unreliable and slower.
-  docker-build-push:
-    strategy:
-      matrix:
-        include:
-          - os: linux
-            arch: arm64
-            build-args: |
-              CGO_CFLAGS
-              CGO_CXXFLAGS
-              GOFLAGS
-          - os: linux
-            arch: amd64
-            build-args: |
-              CGO_CFLAGS
-              CGO_CXXFLAGS
-              GOFLAGS
-          - os: linux
-            arch: amd64
-            suffix: '-rocm'
-            build-args: |
-              CGO_CFLAGS
-              CGO_CXXFLAGS
-              GOFLAGS
-              FLAVOR=rocm
-    runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
-    environment: release
-    needs: setup-environment
-    env:
-      GOFLAGS: ${{ needs.setup-environment.outputs.GOFLAGS }}
-    steps:
-      - uses: actions/checkout@v4
-      - uses: docker/setup-buildx-action@v3
-      - uses: docker/login-action@v3
-        with:
-          username: ${{ vars.DOCKER_USER }}
-          password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
-      - id: build-push
-        uses: docker/build-push-action@v6
-        with:
-          context: .
-          platforms: ${{ matrix.os }}/${{ matrix.arch }}
-          build-args: ${{ matrix.build-args }}
-          outputs: type=image,name=ollama/ollama,push-by-digest=true,name-canonical=true,push=true
-          cache-from: type=registry,ref=ollama/ollama:latest
-          cache-to: type=inline
-      - run: |
-          mkdir -p ${{ matrix.os }}-${{ matrix.arch }}
-          echo "${{ steps.build-push.outputs.digest }}" >${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.suffix }}.txt
-        working-directory: ${{ runner.temp }}
-      - uses: actions/upload-artifact@v4
-        with:
-          name: digest-${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.suffix }}
-          path: |
-            ${{ runner.temp }}/${{ matrix.os }}-${{ matrix.arch }}-${{ matrix.suffix }}.txt
-
-  # Merge Docker images for the same flavor into a single multi-arch manifest
-  docker-merge-push:
-    strategy:
-      matrix:
-        suffix: ['', '-rocm']
     runs-on: linux
-    environment: release
-    needs: [docker-build-push]
+    env:
+      OLLAMA_SKIP_MANIFEST_CREATE: '1'
+      BUILD_ARCH: amd64
+      PUSH: '1'
     steps:
-      - uses: docker/login-action@v3
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
         with:
           username: ${{ vars.DOCKER_USER }}
           password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
-      - id: metadata
-        uses: docker/metadata-action@v4
-        with:
-          flavor: |
-            latest=false
-            suffix=${{ matrix.suffix }}
-          images: |
-            ollama/ollama
-          tags: |
-            type=ref,enable=true,priority=600,prefix=pr-,event=pr
-            type=semver,pattern={{version}}
-      - uses: actions/download-artifact@v4
-        with:
-          pattern: digest-*
-          path: ${{ runner.temp }}
-          merge-multiple: true
       - run: |
-          docker buildx imagetools create $(echo '${{ steps.metadata.outputs.json }}' | jq -cr '.tags | map("-t", .) | join(" ")') $(cat *-${{ matrix.suffix }}.txt | xargs printf 'ollama/ollama@%s ')
-          docker buildx imagetools inspect ollama/ollama:${{ steps.metadata.outputs.version }}
-        working-directory: ${{ runner.temp }}
+          ./scripts/build_linux.sh
+          ./scripts/build_docker.sh
+          mv dist/deps/* dist/
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-linux-amd64
+          path: |
+            dist/*linux*
+            !dist/*-cov
+
+  # Linux ARM assets built using the container based build
+  # (at present, docker isn't pre-installed on arm ubunutu images)
+  build-linux-arm64:
+    environment: release
+    runs-on: linux-arm64
+    env:
+      OLLAMA_SKIP_MANIFEST_CREATE: '1'
+      BUILD_ARCH: arm64
+      PUSH: '1'
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - name: 'Install Docker'
+        run: |
+          # Add Docker's official GPG key:
+          env
+          uname -a
+          sudo apt-get update
+          sudo apt-get install -y ca-certificates curl
+          sudo install -m 0755 -d /etc/apt/keyrings
+          sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
+          sudo chmod a+r /etc/apt/keyrings/docker.asc
+
+          # Add the repository to Apt sources:
+          echo \
+            "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
+            $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
+            sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
+          sudo apt-get update
+          sudo apt-get install -y docker-ce docker-ce-cli containerd.io
+          sudo usermod -aG docker $USER
+          sudo apt-get install acl
+          sudo setfacl --modify user:$USER:rw /var/run/docker.sock
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ vars.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
+      - run: |
+          ./scripts/build_linux.sh
+          ./scripts/build_docker.sh
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-linux-arm64
+          path: |
+            dist/*linux*
+            !dist/*-cov
 
   # Aggregate all the assets and ship a release
   release:
-    needs: [darwin-sign, windows-sign, linux-build]
+    needs:
+      - build-darwin
+      - build-windows
+      - build-linux-amd64
+      - build-linux-arm64
     runs-on: linux
     environment: release
     permissions:
       contents: write
     env:
+      OLLAMA_SKIP_IMAGE_BUILD: '1'
+      PUSH: '1'
       GH_TOKEN: ${{ github.token }}
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/download-artifact@v4
+      - name: Set Version
+        shell: bash
+        run: |
+          echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+          echo "RELEASE_VERSION=$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)" >> $GITHUB_ENV
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
         with:
-          name: dist-darwin
-          path: dist
-      - uses: actions/download-artifact@v4
+          username: ${{ vars.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
+      - run: ./scripts/build_docker.sh
+      - name: Retrieve built artifact
+        uses: actions/download-artifact@v4
         with:
-          name: dist-windows
-          path: dist
-      - uses: actions/download-artifact@v4
-        with:
-          pattern: dist-linux-*
           path: dist
+          pattern: dist-*
           merge-multiple: true
-      - run: find . -type f -not -name 'sha256sum.txt' | xargs sha256sum | tee sha256sum.txt
-        working-directory: dist
+      - run: |
+          ls -lh dist/
+          (cd dist; sha256sum * > sha256sum.txt)
+          cat dist/sha256sum.txt
       - name: Create or update Release
         run: |
-          RELEASE_VERSION="$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)"
-
-          echo "Looking for existing release for ${RELEASE_VERSION}"
-          OLD_TAG=$(gh release ls --json name,tagName | jq -r ".[] | select(.name == \"${RELEASE_VERSION}\") | .tagName")
+          echo "Looking for existing release for ${{ env.RELEASE_VERSION }}"
+          OLD_TAG=$(gh release ls --json name,tagName | jq -r ".[] | select(.name == \"${{ env.RELEASE_VERSION }}\") | .tagName")
           if [ -n "$OLD_TAG" ]; then
-            echo "Updating release ${RELEASE_VERSION} to point to new tag ${GITHUB_REF_NAME}"
+            echo "Updating release ${{ env.RELEASE_VERSION }} to point to new tag ${GITHUB_REF_NAME}"
             gh release edit ${OLD_TAG} --tag ${GITHUB_REF_NAME}
           else
-            echo "Creating new release ${RELEASE_VERSION} pointing to tag ${GITHUB_REF_NAME}"
+            echo "Creating new release ${{ env.RELEASE_VERSION }} pointing to tag ${GITHUB_REF_NAME}"
             gh release create ${GITHUB_REF_NAME} \
-              --title ${RELEASE_VERSION} \
+              --title ${{ env.RELEASE_VERSION }} \
               --draft \
               --generate-notes \
               --prerelease

.github/workflows/test.yaml

@@ -21,7 +21,9 @@ jobs:
   changes:
     runs-on: ubuntu-latest
     outputs:
-      changed: ${{ steps.changes.outputs.changed }}
+      GENERATE: ${{ steps.changes.outputs.GENERATE }}
+      GENERATE_CUDA: ${{ steps.changes.outputs.GENERATE_CUDA }}
+      GENERATE_ROCM: ${{ steps.changes.outputs.GENERATE_ROCM }}
     steps:
       - uses: actions/checkout@v4
         with:
@@ -29,213 +31,293 @@ jobs:
       - id: changes
         run: |
           changed() {
-            local BASE=${{ 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 $GITHUB_OUTPUT
+          {
+            echo GENERATE=$(changed 'llm/llama.cpp' 'llm/patches/**' 'llm/ext_server/**' 'llm/generate/**')
+            echo GENERATE_CUDA=$(changed 'llm/llama.cpp' 'llm/patches/**' 'llm/ext_server/**' 'llm/generate/**')
+            echo GENERATE_ROCM=$(changed 'llm/llama.cpp' 'llm/patches/**' 'llm/ext_server/**' 'llm/generate/**')
+          } >>$GITHUB_OUTPUT
 
-  linux:
+  generate:
     needs: [changes]
-    if: needs.changes.outputs.changed == 'True'
+    if: ${{ needs.changes.outputs.GENERATE == 'True' }}
     strategy:
       matrix:
-        include:
-          - preset: CPU
-          - preset: CUDA
-            container: nvidia/cuda:11.8.0-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'
-    runs-on: linux
-    container: ${{ matrix.container }}
+        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: ${{ matrix.arch }}
+      CGO_ENABLED: '1'
     steps:
       - uses: actions/checkout@v4
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+      - run: go get ./...
       - run: |
-          [ -n "${{ matrix.container }}" ] || sudo=sudo
-          $sudo apt-get update
-          $sudo apt-get install -y cmake ccache ${{ matrix.extra-packages }}
+          $gopath=(get-command go).source | split-path -parent
+          $gccpath=(get-command gcc).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$gccpath;$env:PATH"
+          echo $env:PATH
+          go generate -x ./...
+        if: ${{ startsWith(matrix.os, 'windows-') }}
+        name: 'Windows Go Generate'
+      - run: go generate -x ./...
+        if: ${{ ! startsWith(matrix.os, 'windows-') }}
+        name: 'Unix Go Generate'
+      - run: go build .
+      - uses: actions/upload-artifact@v4
+        with:
+          name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
+          path: |
+            llm/build/**/bin/*
+            llm/build/**/*.a
+  generate-cuda:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.GENERATE_CUDA == 'True' }}
+    strategy:
+      matrix:
+        cuda-version:
+          - '11.8.0'
+    runs-on: linux
+    container: nvidia/cuda:${{ matrix.cuda-version }}-devel-ubuntu20.04
+    steps:
+      - run: |
+          apt-get update && apt-get install -y git build-essential curl
+          curl -fsSL https://github.com/Kitware/CMake/releases/download/v3.28.1/cmake-3.28.1-linux-x86_64.tar.gz \
+            | tar -zx -C /usr --strip-components 1
         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 ${{ matrix.preset }} --parallel
-
-  windows:
+          git config --global --add safe.directory /__w/ollama/ollama
+          go generate -x ./...
+        env:
+          OLLAMA_SKIP_CPU_GENERATE: '1'
+      - uses: actions/upload-artifact@v4
+        with:
+          name: cuda-${{ matrix.cuda-version }}-libraries
+          path: |
+            llm/build/**/bin/*
+            dist/windows-amd64/**
+  generate-rocm:
     needs: [changes]
-    if: needs.changes.outputs.changed == 'True'
+    if: ${{ needs.changes.outputs.GENERATE_ROCM == 'True' }}
     strategy:
       matrix:
-        include:
-          - preset: CPU
-          - preset: CUDA
-            install: https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe
-            flags: '-DCMAKE_CUDA_ARCHITECTURES=80'
-          - preset: ROCm
-            install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
-            flags: '-DAMDGPU_TARGETS=gfx1010'
+        rocm-version:
+          - '6.1.1'
+    runs-on: linux
+    container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
+    steps:
+      - run: |
+          apt-get update && apt-get install -y git build-essential curl rocm-libs
+          curl -fsSL https://github.com/Kitware/CMake/releases/download/v3.28.1/cmake-3.28.1-linux-x86_64.tar.gz \
+            | tar -zx -C /usr --strip-components 1
+        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
+          go generate -x ./...
+        env:
+          OLLAMA_SKIP_CPU_GENERATE: '1'
+      - uses: actions/upload-artifact@v4
+        with:
+          name: rocm-${{ matrix.rocm-version }}-libraries
+          path: |
+            llm/build/**/bin/*
+            dist/windows-amd64/**
+
+  # ROCm generation step
+  generate-windows-rocm:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.GENERATE_ROCM == 'True' }}
     runs-on: windows
     steps:
-      - run: |
-          choco install -y --no-progress ccache ninja
-          ccache -o cache_dir=${{ 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"
-            Start-Process -FilePath .\install.exe -ArgumentList (@("-s", "cudart_11.3", "nvcc_11.3", "cublas_11.3", "cublas_dev_11.3")) -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
-      - 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: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading AMD HIP Installer"
+          Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
+          write-host "Installing AMD HIP"
+          Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
+          write-host "Completed AMD HIP"
+      - name: 'Verify ROCm'
+        run: |
+          & 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
+      - run: go get ./...
       - run: |
-          Import-Module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
-          Enter-VsDevShell -VsInstallPath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
-          cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }}
-          cmake --build --parallel --preset "${{ matrix.preset }}"
+          $gopath=(get-command go).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$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)
+          go generate -x ./...
+        name: go generate
         env:
-          CMAKE_GENERATOR: Ninja
+          OLLAMA_SKIP_CPU_GENERATE: '1'
+      # TODO - do we need any artifacts?
 
-  go_mod_tidy:
-    runs-on: ubuntu-latest
+  # CUDA generation step
+  generate-windows-cuda:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.GENERATE_CUDA == '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: go generate
+        run: |
+          $gopath=(get-command go).source | split-path -parent
+          $cudabin=(get-command nvcc).source | split-path
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$cudabin;$env:PATH"
+          $env:OLLAMA_SKIP_CPU_GENERATE="1"
+          go generate -x ./...
+        env:
+          OLLAMA_SKIP_CPU_GENERATE: '1'
+      # TODO - do we need any artifacts?
 
+  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
+      - run: |
+          mkdir -p llm/build/linux/$ARCH/stub/bin
+          touch llm/build/linux/$ARCH/stub/bin/ollama_llama_server
+        if: ${{ startsWith(matrix.os, 'ubuntu-') }}
+      - run: |
+          mkdir -p llm/build/darwin/$ARCH/stub/bin
+          touch llm/build/darwin/$ARCH/stub/bin/ollama_llama_server
+        if: ${{ startsWith(matrix.os, 'macos-') }}
+      - uses: golangci/golangci-lint-action@v6
+        with:
+          args: --timeout 8m0s -v ${{ startsWith(matrix.os, 'windows-') && '' || '--disable gofmt --disable goimports' }}
   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
-        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
-        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 }}
-
-  patches:
-    runs-on: ubuntu-latest
+      OLLAMA_CPU_TARGET: 'static'
+      OLLAMA_SKIP_CPU_GENERATE: '1'
+      OLLAMA_SKIP_METAL_GENERATE: '1'
     steps:
       - uses: actions/checkout@v4
-      - name: Verify patches apply cleanly and do not change files
-        run: |
-          make -f Makefile.sync clean sync
-          git diff --compact-summary --exit-code
+        with:
+          submodules: recursive
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+      - run: |
+          case ${{ matrix.arch }} in
+            amd64) echo ARCH=x86_64 ;;
+            arm64) echo ARCH=arm64 ;;
+          esac >>$GITHUB_ENV
+        shell: bash
+      - run: |
+          mkdir -p llm/build/linux/$ARCH/stub/bin
+          touch llm/build/linux/$ARCH/stub/bin/ollama_llama_server
+        if: ${{ startsWith(matrix.os, 'ubuntu-') }}
+      - run: |
+          mkdir -p llm/build/darwin/$ARCH/stub/bin
+          touch llm/build/darwin/$ARCH/stub/bin/ollama_llama_server
+        if: ${{ startsWith(matrix.os, 'macos-') }}
+        shell: bash
+      - run: go generate ./...
+      - run: go build
+      - run: go test -v ./...
+      - uses: actions/upload-artifact@v4
+        with:
+          name: ${{ matrix.os }}-binaries
+          path: ollama

.gitignore

@@ -4,13 +4,12 @@
 .venv
 .swp
 dist
-build
+ollama
+ggml-metal.metal
 .cache
 *.exe
 .idea
 test_data
 *.crt
-__debug_bin*
-llama/build
-llama/vendor
-/ollama
+llm/build
+__debug_bin*

.gitmodules

@@ -0,0 +1,4 @@
+[submodule "llama.cpp"]
+	path = llm/llama.cpp
+	url = https://github.com/ggerganov/llama.cpp.git
+	shallow = true

.golangci.yaml

@@ -6,31 +6,23 @@ linters:
     - bidichk
     - bodyclose
     - containedctx
+    - contextcheck
+    - exportloopref
     - gocheckcompilerdirectives
-    - gofmt
-    - gofumpt
-    - gosimple
-    - govet
-    - ineffassign
+    # conditionally enable this on linux/macos
+    # - gofmt
+    # - goimports
     - intrange
-    - makezero
     - misspell
     - nilerr
     - nolintlint
     - nosprintfhostport
-    - staticcheck
-    - tenv
+    - testifylint
     - unconvert
+    - unused
     - wastedassign
     - whitespace
-  disable:
     - usestdlibvars
-    - errcheck
-linters-settings:
-  staticcheck:
-    checks:
-      - all
-      - -SA1019 # omit Deprecated check
 severity:
   default-severity: error
   rules:
@@ -38,4 +30,5 @@ 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

@@ -1,132 +0,0 @@
-cmake_minimum_required(VERSION 3.21)
-
-project(Ollama C CXX)
-
-include(CheckLanguage)
-
-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)
-
-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)
-
-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(${CMAKE_CURRENT_SOURCE_DIR}/ml/backend/ggml/ggml/src/ggml-cpu/amx)
-
-set(GGML_CPU ON)
-add_subdirectory(${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)
-    set(OLLAMA_CUDA_INSTALL_DIR ${OLLAMA_INSTALL_DIR}/cuda_v${CUDAToolkit_VERSION_MAJOR})
-    install(TARGETS ggml-cuda
-        RUNTIME_DEPENDENCIES
-            DIRECTORIES ${CUDAToolkit_BIN_DIR} ${CUDAToolkit_LIBRARY_DIR}
-            PRE_INCLUDE_REGEXES cublas cublasLt cudart
-            PRE_EXCLUDE_REGEXES ".*"
-        RUNTIME DESTINATION ${OLLAMA_CUDA_INSTALL_DIR} COMPONENT CUDA
-        LIBRARY DESTINATION ${OLLAMA_CUDA_INSTALL_DIR} COMPONENT CUDA
-    )
-endif()
-
-set(WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX "^gfx(906|908|90a|1200|1201):xnack[+-]$"
-    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_DEPENDENCIES
-                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

@@ -1,110 +0,0 @@
-{
-  "version": 3,
-  "configurePresets": [
-    {
-      "name": "Default",
-      "binaryDir": "${sourceDir}/build",
-      "installDir": "${sourceDir}/dist",
-      "cacheVariables": {
-        "CMAKE_BUILD_TYPE": "Release"
-      }
-    },
-    {
-      "name": "CPU",
-      "inherits": [ "Default" ]
-    },
-    {
-      "name": "CUDA",
-      "inherits": [ "Default" ]
-    },
-    {
-      "name": "CUDA 11",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "50;52;53;60;61;70;75;80;86"
-      }
-    },
-    {
-      "name": "CUDA 12",
-      "inherits": [ "CUDA" ],
-      "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "50;60;61;70;75;80;86;87;89;90;90a;120"
-      }
-    },
-    {
-      "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": {
-        "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": "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

@@ -1,88 +0,0 @@
-# Contributing to Ollama
-
-Thank you for your interest in contributing to Ollama! Here are a few guidelines to help get you started.
-
-## Set up
-
-See the [development documentation](./docs/development.md) for instructions on how to build and run Ollama locally.
-
-### 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.
-* [Performance](https://github.com/ollama/ollama/issues?q=is%3Aissue+is%3Aopen+label%3Aperformance): issues to make Ollama faster at model inference, downloading or uploading.
-* [Security](https://github.com/ollama/ollama/blob/main/SECURITY.md): issues that could lead to a security vulnerability. As mentioned in [SECURITY.md](https://github.com/ollama/ollama/blob/main/SECURITY.md), please do not disclose security vulnerabilities publicly.
-
-### Issues that are harder to review
-
-* New features: new features (e.g. API fields, environment variables) add surface area to Ollama and make it harder to maintain in the long run as they cannot be removed without potentially breaking users in the future.
-* Refactoring: large code improvements are important, but can be harder or take longer to review and merge.
-* Documentation: small updates to fill in or correct missing documentation is helpful, however large documentation additions can be hard to maintain over time.
-
-### Issues that may not be accepted
-
-* Changes that break backwards compatibility in Ollama's API (including the OpenAI-compatible API)
-* 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
-
-> 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 clairity on good commit messages, and bad
-
-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.
-
-## Need help?
-
-If you need help with anything, feel free to reach out to us on our [Discord server](https://discord.gg/ollama).

Dockerfile

@@ -1,131 +1,144 @@
-# vim: filetype=dockerfile
+ARG GOLANG_VERSION=1.22.1
+ARG CMAKE_VERSION=3.22.1
+# this CUDA_VERSION corresponds with the one specified in docs/gpu.md
+ARG CUDA_VERSION=11.3.1
+ARG ROCM_VERSION=6.1.1
 
-ARG FLAVOR=${TARGETARCH}
+# Copy the minimal context we need to run the generate scripts
+FROM scratch AS llm-code
+COPY .git .git
+COPY .gitmodules .gitmodules
+COPY llm llm
 
-ARG ROCMVERSION=6.3.3
-ARG JETPACK5VERSION=r35.4.1
-ARG JETPACK6VERSION=r36.4.0
-ARG CMAKEVERSION=3.31.2
+FROM --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION-devel-centos7 AS cuda-build-amd64
+ARG CMAKE_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
+WORKDIR /go/src/github.com/ollama/ollama/llm/generate
+ARG CGO_CFLAGS
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
 
-# CUDA v11 requires gcc v10.  v10.3 has regressions, so the rockylinux 8.5 AppStream has the latest compatible version
-FROM --platform=linux/amd64 rocm/dev-almalinux-8:${ROCMVERSION}-complete AS base-amd64
-RUN yum install -y yum-utils \
-    && yum-config-manager --add-repo https://dl.rockylinux.org/vault/rocky/8.5/AppStream/\$basearch/os/ \
-    && rpm --import https://dl.rockylinux.org/pub/rocky/RPM-GPG-KEY-Rocky-8 \
-    && dnf install -y yum-utils ccache gcc-toolset-10-gcc-10.2.1-8.2.el8 gcc-toolset-10-gcc-c++-10.2.1-8.2.el8 gcc-toolset-10-binutils-2.35-11.el8 \
-    && yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
-ENV PATH=/opt/rh/gcc-toolset-10/root/usr/bin:$PATH
+FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION-devel-rockylinux8 AS cuda-build-arm64
+ARG CMAKE_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
+WORKDIR /go/src/github.com/ollama/ollama/llm/generate
+ARG CGO_CFLAGS
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
 
-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 --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS rocm-build-amd64
+ARG CMAKE_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+ENV LIBRARY_PATH /opt/amdgpu/lib64
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
+WORKDIR /go/src/github.com/ollama/ollama/llm/generate
+ARG CGO_CFLAGS
+ARG AMDGPU_TARGETS
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
+RUN mkdir /tmp/scratch && \
+    for dep in $(zcat /go/src/github.com/ollama/ollama/llm/build/linux/x86_64/rocm*/bin/deps.txt.gz) ; do \
+        cp ${dep} /tmp/scratch/ || exit 1 ; \
+    done && \
+    (cd /opt/rocm/lib && tar cf - rocblas/library) | (cd /tmp/scratch/ && tar xf - ) && \
+    mkdir -p /go/src/github.com/ollama/ollama/dist/deps/ && \
+    (cd /tmp/scratch/ && tar czvf /go/src/github.com/ollama/ollama/dist/deps/ollama-linux-amd64-rocm.tgz . )
 
-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:$PATH
-RUN --mount=type=cache,target=/root/.ccache \
-    cmake --preset 'CPU' \
-        && cmake --build --parallel --preset 'CPU' \
-        && cmake --install build --component CPU --strip --parallel 8
+FROM --platform=linux/amd64 centos:7 AS cpu-builder-amd64
+ARG CMAKE_VERSION
+ARG GOLANG_VERSION
+COPY ./scripts/rh_linux_deps.sh /
+RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
+ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
+ARG OLLAMA_CUSTOM_CPU_DEFS
+ARG CGO_CFLAGS
+WORKDIR /go/src/github.com/ollama/ollama/llm/generate
 
-FROM base AS cuda-11
-ARG CUDA11VERSION=11.3
-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' \
-        && cmake --build --parallel --preset 'CUDA 11' \
-        && cmake --install build --component CUDA --strip --parallel 8
+FROM --platform=linux/amd64 cpu-builder-amd64 AS static-build-amd64
+RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
+FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
+FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
+FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
 
-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' \
-        && cmake --build --parallel --preset 'CUDA 12' \
-        && cmake --install build --component CUDA --strip --parallel 8
+FROM --platform=linux/arm64 rockylinux:8 AS cpu-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
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
+ARG OLLAMA_CUSTOM_CPU_DEFS
+ARG CGO_CFLAGS
+WORKDIR /go/src/github.com/ollama/ollama/llm/generate
 
-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 cpu-builder-arm64 AS static-build-arm64
+RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
+FROM --platform=linux/arm64 cpu-builder-arm64 AS cpu-build-arm64
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
 
-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
+# Intermediate stage used for ./scripts/build_linux.sh
+FROM --platform=linux/amd64 cpu-build-amd64 AS build-amd64
+ENV CGO_ENABLED 1
 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
 COPY . .
-ARG GOFLAGS="'-ldflags=-w -s'"
-ENV CGO_ENABLED=1
-RUN --mount=type=cache,target=/root/.cache/go-build \
-    go build -trimpath -buildmode=pie -o /bin/ollama .
+COPY --from=static-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cpu_avx-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cpu_avx2-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cuda-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/dist/deps/ ./dist/deps/
+ARG GOFLAGS
+ARG CGO_CFLAGS
+RUN go build -trimpath .
 
-FROM --platform=linux/amd64 scratch AS amd64
-COPY --from=cuda-11 dist/lib/ollama/cuda_v11 /lib/ollama/cuda_v11
-COPY --from=cuda-12 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_v12
+# Intermediate stage used for ./scripts/build_linux.sh
+FROM --platform=linux/arm64 cpu-build-arm64 AS build-arm64
+ENV CGO_ENABLED 1
+ARG GOLANG_VERSION
+WORKDIR /go/src/github.com/ollama/ollama
+COPY . .
+COPY --from=static-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cuda-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+ARG GOFLAGS
+ARG CGO_CFLAGS
+RUN go build -trimpath .
 
-FROM --platform=linux/arm64 scratch AS arm64
-COPY --from=cuda-11 dist/lib/ollama/cuda_v11 /lib/ollama/cuda_v11
-COPY --from=cuda-12 dist/lib/ollama/cuda_v12 /lib/ollama/cuda_v12
-COPY --from=jetpack-5 dist/lib/ollama/cuda_v11 lib/ollama/cuda_jetpack5
-COPY --from=jetpack-6 dist/lib/ollama/cuda_v12 lib/ollama/cuda_jetpack6
+# Runtime stages
+FROM --platform=linux/amd64 ubuntu:22.04 as runtime-amd64
+RUN apt-get update && apt-get install -y ca-certificates
+COPY --from=build-amd64 /go/src/github.com/ollama/ollama/ollama /bin/ollama
+FROM --platform=linux/arm64 ubuntu:22.04 as runtime-arm64
+RUN apt-get update && apt-get install -y ca-certificates
+COPY --from=build-arm64 /go/src/github.com/ollama/ollama/ollama /bin/ollama
 
-FROM scratch AS rocm
-COPY --from=rocm-6 dist/lib/ollama/rocm /lib/ollama/rocm
+# Radeon images are much larger so we keep it distinct from the CPU/CUDA image
+FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete as runtime-rocm
+RUN update-pciids
+COPY --from=build-amd64 /go/src/github.com/ollama/ollama/ollama /bin/ollama
+EXPOSE 11434
+ENV OLLAMA_HOST 0.0.0.0
 
-FROM ${FLAVOR} AS archive
-COPY --from=cpu dist/lib/ollama /lib/ollama
-COPY --from=build /bin/ollama /bin/ollama
+ENTRYPOINT ["/bin/ollama"]
+CMD ["serve"]
 
-FROM ubuntu:20.04
-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
+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.sync

@@ -1,60 +0,0 @@
-UPSTREAM=https://github.com/ggerganov/llama.cpp.git
-WORKDIR=llama/vendor
-FETCH_HEAD=d7cfe1ffe0f435d0048a6058d529daf76e072d9c
-
-.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 $(MAKEFILE_LIST)) clean sync"
-
-.PHONY: sync
-sync: llama/build-info.cpp llama/llama.cpp ml/backend/ggml/ggml apply-patches
-
-.PHONY: llama/build-info.cpp
-llama/build-info.cpp: llama/build-info.cpp.in
-	sed -e 's|@FETCH_HEAD@|$(FETCH_HEAD)|' $< > $@
-
-.PHONY: llama/llama.cpp
-llama/llama.cpp: llama/vendor/ apply-patches
-	rsync -arvzc -f "merge $@/.rsync-filter" $< $@
-
-.PHONY: ml/backend/ggml/ggml apply-patches
-ml/backend/ggml/ggml: llama/vendor/ggml/ apply-patches
-	rsync -arvzc -f "merge $@/.rsync-filter" $< $@
-
-PATCHES=$(wildcard llama/patches/*.patch)
-
-.PHONY: apply-patches
-.NOTPARALLEL:
-apply-patches: $(addsuffix ed, $(PATCHES))
-
-%.patched: %.patch
-	@if git -c user.name=nobody -c 'user.email=<>' -C $(WORKDIR) am -3 $(realpath $<); then touch $@; else git -C $(WORKDIR) am --abort; 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
-	$(RM) $(addsuffix ed, $(PATCHES))

README.md

@@ -1,24 +1,24 @@
 <div align="center">
-  <a href="https://ollama.com">
-    <img alt="ollama" height="200px" 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-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 [Llama 3.2](https://ollama.com/library/llama3.2):
+To run and chat with [Llama 3](https://ollama.com/library/llama3):
 
-```shell
-ollama run llama3.2
+```
+ollama run llama3
 ```
 
 ## Model library
@@ -52,35 +47,24 @@ 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 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-3.2         | 8B         | 4.9GB | `ollama run granite3.2`          |
+| Model              | Parameters | Size  | Download                       |
+| ------------------ | ---------- | ----- | ------------------------------ |
+| Llama 3            | 8B         | 4.7GB | `ollama run llama3`            |
+| Llama 3            | 70B        | 40GB  | `ollama run llama3:70b`        |
+| Phi 3 Mini         | 3.8B       | 2.3GB | `ollama run phi3`              |
+| Phi 3 Medium       | 14B        | 7.9GB | `ollama run phi3:medium`       |
+| 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.
+> 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.
 
 ## Customize a model
 
@@ -96,32 +80,32 @@ 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.
 
 ### Customize a prompt
 
-Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3.2` model:
+Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3` model:
 
-```shell
-ollama pull llama3.2
+```
+ollama pull llama3
 ```
 
 Create a `Modelfile`:
 
 ```
-FROM llama3.2
+FROM llama3
 
 # set the temperature to 1 [higher is more creative, lower is more coherent]
 PARAMETER temperature 1
@@ -141,7 +125,7 @@ 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
 
@@ -149,28 +133,28 @@ 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
+```
+ollama pull llama3
 ```
 
 > This command can also be used to update a local model. Only the diff will be pulled.
 
 ### Remove a model
 
-```shell
-ollama rm llama3.2
+```
+ollama rm llama3
 ```
 
 ### Copy a model
 
-```shell
-ollama cp llama3.2 my-model
+```
+ollama cp llama3 my-model
 ```
 
 ### Multiline input
@@ -187,43 +171,29 @@ I'm a basic program that prints the famous "Hello, world!" message to the consol
 ### Multimodal models
 
 ```
-ollama run llava "What's in this image? /Users/jmorgan/Desktop/smile.png"
+>>> 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 "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
+```
+ollama show llama3
 ```
 
 ### 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
-```
-
 ### Start Ollama
 
 `ollama serve` is used when you want to start ollama without running the desktop application.
@@ -236,14 +206,14 @@ 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
+```
+./ollama run llama3
 ```
 
 ## REST API
@@ -252,18 +222,18 @@ Ollama has a REST API for running and managing models.
 
 ### Generate a response
 
-```shell
+```
 curl http://localhost:11434/api/generate -d '{
-  "model": "llama3.2",
+  "model": "llama3",
   "prompt":"Why is the sky blue?"
 }'
 ```
 
 ### Chat with a model
 
-```shell
+```
 curl http://localhost:11434/api/chat -d '{
-  "model": "llama3.2",
+  "model": "llama3",
   "messages": [
     { "role": "user", "content": "why is the sky blue?" }
   ]
@@ -277,7 +247,6 @@ 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)
@@ -285,7 +254,6 @@ 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)
@@ -311,8 +279,7 @@ 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)
-- [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)
@@ -322,95 +289,16 @@ 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 )
 - [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)
-- [Sidellama](https://github.com/gyopak/sidellama) (browser-based LLM client)
-- [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
-- [PyOllaMx](https://github.com/kspviswa/pyOllaMx) - macOS application capable of chatting with both Ollama and Apple MLX models.
-- [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)
-- [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 on Mac/Windows/Linux)
-- [OrionChat](https://github.com/EliasPereirah/OrionChat) - OrionChat is a web interface for chatting with different AI providers
-- [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 equivent 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.)
-- [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)
-
-### 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)
@@ -420,7 +308,7 @@ 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)
@@ -428,62 +316,31 @@ 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.
-
-### 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)
-- [Flox](https://flox.dev/blog/ollama-part-one)
 
 ### Libraries
 
-- [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)
+- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama) with [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
 - [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)
+- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
 - [LiteLLM](https://github.com/BerriAI/litellm)
-- [OllamaFarm for Go](https://github.com/presbrey/ollamafarm)
 - [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
 - [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
 - [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs)
 - [Ollama-hpp for C++](https://github.com/jmont-dev/ollama-hpp)
-- [Ollama4j for Java](https://github.com/ollama4j/ollama4j)
+- [Ollama4j for Java](https://github.com/amithkoujalgi/ollama4j)
 - [ModelFusion Typescript Library](https://modelfusion.dev/integration/model-provider/ollama)
 - [OllamaKit for Swift](https://github.com/kevinhermawan/OllamaKit)
 - [Ollama for Dart](https://github.com/breitburg/dart-ollama)
@@ -500,42 +357,17 @@ 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 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)
 
 ### 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.)
 
 ### 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)
@@ -552,38 +384,15 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [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)
 - [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)
+- [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and HuggingFace)
 - [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
-- [Plasmoid Ollama Control](https://github.com/imoize/plasmoid-ollamacontrol) (KDE Plasma extension that allows you to quickly manage/control Ollama model)
 - [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 depends 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.)
-- [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)
 
 ### Supported backends
 
 - [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.

SECURITY.md

@@ -1,25 +0,0 @@
-# Security
-
-The Ollama maintainer team takes security seriously and will actively work to resolve security issues.
-
-## Reporting a vulnerability
-
-If you discover a security vulnerability, please do not open a public issue. Instead, please report it by emailing hello@ollama.com. We ask that you give us sufficient time to investigate and address the vulnerability before disclosing it publicly.
-
-Please include the following details in your report:
-- A description of the vulnerability
-- Steps to reproduce the issue
-- Your assessment of the potential impact
-- Any possible mitigations
-
-## Security best practices
-
-While the maintainer team does their best to secure Ollama, users are encouraged to implement their own security best practices, such as:
-
-- Regularly updating to the latest version of Ollama
-- Securing access to hosted instances of Ollama
-- Monitoring systems for unusual activity
-
-## Contact
-
-For any other questions or concerns related to security, please contact us at hello@ollama.com

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 (
@@ -18,9 +18,9 @@ import (
 	"bytes"
 	"context"
 	"encoding/json"
-	"errors"
 	"fmt"
 	"io"
+	"net"
 	"net/http"
 	"net/url"
 	"runtime"
@@ -55,7 +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>
@@ -63,8 +63,13 @@ func checkError(resp *http.Response, body []byte) error {
 // If the variable is not specified, a default ollama host and port will be
 // used.
 func ClientFromEnvironment() (*Client, error) {
+	ollamaHost := envconfig.Host
+
 	return &Client{
-		base: envconfig.Host(),
+		base: &url.URL{
+			Scheme: ollamaHost.Scheme,
+			Host:   net.JoinHostPort(ollamaHost.Host, ollamaHost.Port),
+		},
 		http: http.DefaultClient,
 	}, nil
 }
@@ -132,7 +137,7 @@ 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 {
@@ -173,7 +178,7 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 		}
 
 		if errorResponse.Error != "" {
-			return errors.New(errorResponse.Error)
+			return fmt.Errorf(errorResponse.Error)
 		}
 
 		if response.StatusCode >= http.StatusBadRequest {
@@ -298,7 +303,7 @@ func (c *Client) List(ctx context.Context) (*ListResponse, error) {
 	return &lr, nil
 }
 
-// ListRunning lists running models.
+// List running models.
 func (c *Client) ListRunning(ctx context.Context) (*ProcessResponse, error) {
 	var lr ProcessResponse
 	if err := c.do(ctx, http.MethodGet, "/api/ps", nil, &lr); err != nil {
@@ -333,7 +338,7 @@ func (c *Client) Show(ctx context.Context, req *ShowRequest) (*ShowResponse, err
 	return &resp, nil
 }
 
-// Heartbeat checks if the server has started and is responsive; if yes, it
+// Hearbeat checks if the server has started and is responsive; if yes, it
 // returns nil, otherwise an error.
 func (c *Client) Heartbeat(ctx context.Context) error {
 	if err := c.do(ctx, http.MethodHead, "/", nil, nil); err != nil {
@@ -342,16 +347,7 @@ func (c *Client) Heartbeat(ctx context.Context) error {
 	return nil
 }
 
-// Embed generates embeddings from a model.
-func (c *Client) Embed(ctx context.Context, req *EmbedRequest) (*EmbedResponse, error) {
-	var resp EmbedResponse
-	if err := c.do(ctx, http.MethodPost, "/api/embed", req, &resp); err != nil {
-		return nil, err
-	}
-	return &resp, nil
-}
-
-// Embeddings generates an embedding from a model.
+// Embeddings generates embeddings from a model.
 func (c *Client) Embeddings(ctx context.Context, req *EmbeddingRequest) (*EmbeddingResponse, error) {
 	var resp EmbeddingResponse
 	if err := c.do(ctx, http.MethodPost, "/api/embeddings", req, &resp); err != nil {

api/client_test.go

@@ -1,14 +1,9 @@
 package api
 
 import (
-	"context"
-	"encoding/json"
-	"fmt"
-	"net/http"
-	"net/http/httptest"
-	"net/url"
-	"strings"
 	"testing"
+
+	"github.com/ollama/ollama/envconfig"
 )
 
 func TestClientFromEnvironment(t *testing.T) {
@@ -38,6 +33,7 @@ func TestClientFromEnvironment(t *testing.T) {
 	for k, v := range testCases {
 		t.Run(k, func(t *testing.T) {
 			t.Setenv("OLLAMA_HOST", v.value)
+			envconfig.LoadConfig()
 
 			client, err := ClientFromEnvironment()
 			if err != v.err {
@@ -50,206 +46,3 @@ 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: "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(context.Background(), 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(context.Background(), 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
@@ -50,9 +47,6 @@ type GenerateRequest struct {
 	// Prompt is the textual prompt to send to the model.
 	Prompt string `json:"prompt"`
 
-	// Suffix is the text that comes after the inserted text.
-	Suffix string `json:"suffix"`
-
 	// System overrides the model's default system message/prompt.
 	System string `json:"system"`
 
@@ -60,7 +54,7 @@ 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.
@@ -70,7 +64,7 @@ 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.
@@ -82,7 +76,7 @@ type GenerateRequest struct {
 
 	// 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"`
+	Options map[string]interface{} `json:"options"`
 }
 
 // ChatRequest describes a request sent by [Client.Chat].
@@ -93,96 +87,27 @@ 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"`
-}
-
-type Tools []Tool
-
-func (t Tools) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
-}
-
-func (t Tool) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
+	Options map[string]interface{} `json:"options"`
 }
 
 // Message is a single message in a chat sequence. The message contains the
 // role ("system", "user", or "assistant"), the content and an optional list
 // of images.
 type Message struct {
-	Role      string      `json:"role"`
-	Content   string      `json:"content"`
-	Images    []ImageData `json:"images,omitempty"`
-	ToolCalls []ToolCall  `json:"tool_calls,omitempty"`
-}
-
-func (m *Message) UnmarshalJSON(b []byte) error {
-	type Alias Message
-	var a Alias
-	if err := json.Unmarshal(b, &a); err != nil {
-		return err
-	}
-
-	*m = Message(a)
-	m.Role = strings.ToLower(m.Role)
-	return nil
-}
-
-type ToolCall struct {
-	Function ToolCallFunction `json:"function"`
-}
-
-type ToolCallFunction struct {
-	Index     int                       `json:"index,omitempty"`
-	Name      string                    `json:"name"`
-	Arguments ToolCallFunctionArguments `json:"arguments"`
-}
-
-type ToolCallFunctionArguments map[string]any
-
-func (t *ToolCallFunctionArguments) String() string {
-	bts, _ := json.Marshal(t)
-	return string(bts)
-}
-
-type Tool struct {
-	Type     string       `json:"type"`
-	Function ToolFunction `json:"function"`
-}
-
-type ToolFunction struct {
-	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 {
-	bts, _ := json.Marshal(t)
-	return string(bts)
+	Role    string      `json:"role"`
+	Content string      `json:"content"`
+	Images  []ImageData `json:"images,omitempty"`
 }
 
 // ChatResponse is the response returned by [Client.Chat]. Its fields are
@@ -207,8 +132,8 @@ 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
 
@@ -218,7 +143,7 @@ type Options struct {
 	NumPredict       int      `json:"num_predict,omitempty"`
 	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"`
@@ -228,17 +153,19 @@ type Options struct {
 	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"`
 }
 
 // Runner options which must be set when the model is loaded into memory
 type Runner struct {
+	UseNUMA   bool  `json:"numa,omitempty"`
 	NumCtx    int   `json:"num_ctx,omitempty"`
 	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"` // Deprecated: This option is ignored
+	F16KV     bool  `json:"f16_kv,omitempty"`
 	LogitsAll bool  `json:"logits_all,omitempty"`
 	VocabOnly bool  `json:"vocab_only,omitempty"`
 	UseMMap   *bool `json:"use_mmap,omitempty"`
@@ -246,34 +173,6 @@ type Runner struct {
 	NumThread int   `json:"num_thread,omitempty"`
 }
 
-// EmbedRequest is the request passed to [Client.Embed].
-type EmbedRequest struct {
-	// Model is the model name.
-	Model string `json:"model"`
-
-	// Input is the input to embed.
-	Input any `json:"input"`
-
-	// KeepAlive controls how long the model will stay loaded in memory following
-	// this request.
-	KeepAlive *Duration `json:"keep_alive,omitempty"`
-
-	Truncate *bool `json:"truncate,omitempty"`
-
-	// Options lists model-specific options.
-	Options map[string]any `json:"options"`
-}
-
-// EmbedResponse is the response from [Client.Embed].
-type EmbedResponse struct {
-	Model      string      `json:"model"`
-	Embeddings [][]float32 `json:"embeddings"`
-
-	TotalDuration   time.Duration `json:"total_duration,omitempty"`
-	LoadDuration    time.Duration `json:"load_duration,omitempty"`
-	PromptEvalCount int           `json:"prompt_eval_count,omitempty"`
-}
-
 // EmbeddingRequest is the request passed to [Client.Embeddings].
 type EmbeddingRequest struct {
 	// Model is the model name.
@@ -287,7 +186,7 @@ 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].
@@ -297,22 +196,16 @@ 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"`
+	Model     string `json:"model"`
+	Path      string `json:"path"`
+	Modelfile string `json:"modelfile"`
+	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"`
-
-	// Deprecated: set the model name with Model instead
+	// Name is deprecated, see Model
 	Name string `json:"name"`
-	// Deprecated: use Quantize instead
+
+	// Quantization is deprecated, see Quantize
 	Quantization string `json:"quantization,omitempty"`
 }
 
@@ -320,39 +213,35 @@ type CreateRequest struct {
 type DeleteRequest struct {
 	Model string `json:"model"`
 
-	// Deprecated: set the model name with Model instead
+	// Name is deprecated, see Model
 	Name string `json:"name"`
 }
 
 // ShowRequest is the request passed to [Client.Show].
 type ShowRequest struct {
-	Model  string `json:"model"`
-	System string `json:"system"`
-
-	// Template is deprecated
+	Model    string `json:"model"`
+	System   string `json:"system"`
 	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 is deprecated, see Model
 	Name string `json:"name"`
 }
 
 // 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].
@@ -364,12 +253,12 @@ 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
+	// Name is deprecated, see Model
 	Name string `json:"name"`
 }
 
@@ -390,7 +279,7 @@ type PushRequest struct {
 	Password string `json:"password"`
 	Stream   *bool  `json:"stream,omitempty"`
 
-	// Deprecated: set the model name with Model instead
+	// Name is deprecated, see Model
 	Name string `json:"name"`
 }
 
@@ -470,13 +359,6 @@ 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)
@@ -505,7 +387,7 @@ 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
 
@@ -521,7 +403,7 @@ func (opts *Options) FromMap(m map[string]any) error {
 	for key, val := range m {
 		opt, ok := jsonOpts[key]
 		if !ok {
-			slog.Warn("invalid option provided", "option", key)
+			slog.Warn("invalid option provided", "option", opt.Name)
 			continue
 		}
 
@@ -562,12 +444,12 @@ 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)
@@ -609,6 +491,7 @@ func DefaultOptions() Options {
 		Temperature:      0.8,
 		TopK:             40,
 		TopP:             0.9,
+		TFSZ:             1.0,
 		TypicalP:         1.0,
 		RepeatLastN:      64,
 		RepeatPenalty:    1.1,
@@ -617,17 +500,20 @@ func DefaultOptions() Options {
 		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,
+			UseNUMA:   false,
 		},
 	}
 }
@@ -674,7 +560,7 @@ 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
@@ -688,7 +574,7 @@ 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

@@ -2,7 +2,7 @@ package api
 
 import (
 	"encoding/json"
-	"errors"
+	"fmt"
 	"math"
 	"testing"
 	"time"
@@ -134,7 +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()
@@ -192,7 +192,7 @@ func TestUseMmapFormatParams(t *testing.T) {
 				"use_mmap": {"foo"},
 			},
 			exp: nil,
-			err: errors.New("invalid bool value [foo]"),
+			err: fmt.Errorf("invalid bool value [foo]"),
 		},
 	}
 
@@ -208,26 +208,3 @@ func TestUseMmapFormatParams(t *testing.T) {
 		})
 	}
 }
-
-func TestMessage_UnmarshalJSON(t *testing.T) {
-	tests := []struct {
-		input    string
-		expected string
-	}{
-		{`{"role": "USER", "content": "Hello!"}`, "user"},
-		{`{"role": "System", "content": "Initialization complete."}`, "system"},
-		{`{"role": "assistant", "content": "How can I help you?"}`, "assistant"},
-		{`{"role": "TOOl", "content": "Access granted."}`, "tool"},
-	}
-
-	for _, test := range tests {
-		var msg Message
-		if err := json.Unmarshal([]byte(test.input), &msg); err != nil {
-			t.Errorf("Unexpected error: %v", err)
-		}
-
-		if msg.Role != test.expected {
-			t.Errorf("role not lowercased: got %v, expected %v", msg.Role, test.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/getstarted_nonwindows.go

@@ -2,8 +2,8 @@
 
 package lifecycle
 
-import "errors"
+import "fmt"
 
 func GetStarted() error {
-	return errors.New("not implemented")
+	return fmt.Errorf("GetStarted not implemented")
 }

app/lifecycle/getstarted_windows.go

@@ -34,6 +34,7 @@ func GetStarted() error {
 		Sys:   &syscall.SysProcAttr{CreationFlags: CREATE_NEW_CONSOLE, HideWindow: false},
 	}
 	proc, err := os.StartProcess(args[0], args, attrs)
+
 	if err != nil {
 		return fmt.Errorf("unable to start getting started shell %w", err)
 	}

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

@@ -14,7 +14,7 @@ import (
 func InitLogging() {
 	level := slog.LevelInfo
 
-	if envconfig.Debug() {
+	if envconfig.Debug {
 		level = slog.LevelDebug
 	}
 
@@ -27,7 +27,7 @@ func InitLogging() {
 		// TODO - write one-line to the app.log file saying we're running in console mode to help avoid confusion
 	} else {
 		rotateLogs(AppLogFile)
-		logFile, err = os.OpenFile(AppLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0o755)
+		logFile, err = os.OpenFile(AppLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
 		if err != nil {
 			slog.Error(fmt.Sprintf("failed to create server log %v", err))
 			return

app/lifecycle/logging_nonwindows.go

@@ -5,5 +5,5 @@ package lifecycle
 import "log/slog"
 
 func ShowLogs() {
-	slog.Warn("not implemented")
+	slog.Warn("ShowLogs not yet implemented")
 }

app/lifecycle/logging_test.go

@@ -17,7 +17,7 @@ func TestRotateLogs(t *testing.T) {
 	// No log exists
 	rotateLogs(logFile)
 
-	require.NoError(t, os.WriteFile(logFile, []byte("1"), 0o644))
+	require.NoError(t, os.WriteFile(logFile, []byte("1"), 0644))
 	assert.FileExists(t, logFile)
 	// First rotation
 	rotateLogs(logFile)
@@ -32,7 +32,7 @@ func TestRotateLogs(t *testing.T) {
 	assert.NoFileExists(t, logFile)
 
 	for i := 2; i <= LogRotationCount+1; i++ {
-		require.NoError(t, os.WriteFile(logFile, []byte(strconv.Itoa(i)), 0o644))
+		require.NoError(t, os.WriteFile(logFile, []byte(strconv.Itoa(i)), 0644))
 		assert.FileExists(t, logFile)
 		rotateLogs(logFile)
 		assert.NoFileExists(t, logFile)

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 {
@@ -61,7 +55,7 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
 	}
 
 	rotateLogs(ServerLogFile)
-	logFile, err := os.OpenFile(ServerLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0o755)
+	logFile, err := os.OpenFile(ServerLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0755)
 	if err != nil {
 		return nil, fmt.Errorf("failed to create server log: %w", err)
 	}

app/lifecycle/updater.go

@@ -15,7 +15,6 @@ import (
 	"path"
 	"path/filepath"
 	"runtime"
-	"strconv"
 	"strings"
 	"time"
 
@@ -47,7 +46,7 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
 	query.Add("os", runtime.GOOS)
 	query.Add("arch", runtime.GOARCH)
 	query.Add("version", version.Version)
-	query.Add("ts", strconv.FormatInt(time.Now().Unix(), 10))
+	query.Add("ts", fmt.Sprintf("%d", time.Now().Unix()))
 
 	nonce, err := auth.NewNonce(rand.Reader, 16)
 	if err != nil {

app/lifecycle/updater_nonwindows.go

@@ -4,9 +4,9 @@ package lifecycle
 
 import (
 	"context"
-	"errors"
+	"fmt"
 )
 
 func DoUpgrade(cancel context.CancelFunc, done chan int) error {
-	return errors.New("not implemented")
+	return fmt.Errorf("DoUpgrade not yet implemented")
 }

app/lifecycle/updater_windows.go

@@ -2,7 +2,6 @@ package lifecycle
 
 import (
 	"context"
-	"errors"
 	"fmt"
 	"log/slog"
 	"os"
@@ -16,7 +15,7 @@ func DoUpgrade(cancel context.CancelFunc, done chan int) error {
 		return fmt.Errorf("failed to lookup downloads: %s", err)
 	}
 	if len(files) == 0 {
-		return errors.New("no update downloads found")
+		return fmt.Errorf("no update downloads found")
 	} else if len(files) > 1 {
 		// Shouldn't happen
 		slog.Warn(fmt.Sprintf("multiple downloads found, using first one %v", files))
@@ -26,15 +25,19 @@ 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")
@@ -61,7 +64,7 @@ func DoUpgrade(cancel context.CancelFunc, done chan int) error {
 		}
 	} else {
 		// TODO - some details about why it didn't start, or is this a pedantic error case?
-		return errors.New("installer process did not start")
+		return fmt.Errorf("installer process did not start")
 	}
 
 	// TODO should we linger for a moment and check to make sure it's actually running by checking the pid?

app/ollama.iss

@@ -28,8 +28,8 @@ AppPublisher={#MyAppPublisher}
 AppPublisherURL={#MyAppURL}
 AppSupportURL={#MyAppURL}
 AppUpdatesURL={#MyAppURL}
-ArchitecturesAllowed=x64compatible arm64
-ArchitecturesInstallIn64BitMode=x64compatible arm64
+ArchitecturesAllowed=x64 arm64
+ArchitecturesInstallIn64BitMode=x64 arm64
 DefaultDirName={localappdata}\Programs\{#MyAppName}
 DefaultGroupName={#MyAppName}
 DisableProgramGroupPage=yes
@@ -48,13 +48,12 @@ OutputDir=..\dist\
 SetupLogging=yes
 CloseApplications=yes
 RestartApplications=no
-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
@@ -87,20 +86,21 @@ Name: "english"; MessagesFile: "compiler:Default.isl"
 DialogFontSize=12
 
 [Files]
-#if DirExists("..\dist\windows-amd64")
-Source: "..\dist\windows-amd64-app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ;Check: not IsArm64();  Flags: ignoreversion 64bit
-Source: "..\dist\windows-amd64\ollama.exe"; DestDir: "{app}"; Check: not IsArm64(); Flags: ignoreversion 64bit
-Source: "..\dist\windows-amd64\lib\ollama\*"; DestDir: "{app}\lib\ollama\"; Check: not IsArm64(); Flags: ignoreversion 64bit recursesubdirs
-#endif
-
-#if DirExists("..\dist\windows-arm64")
-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
-#endif
-
+Source: ".\app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ; Flags: ignoreversion 64bit
+Source: "..\ollama.exe"; DestDir: "{app}"; Flags: ignoreversion 64bit
+Source: "..\dist\windows-{#ARCH}\ollama_runners\*"; DestDir: "{app}\ollama_runners"; Flags: ignoreversion 64bit recursesubdirs
 Source: "..\dist\ollama_welcome.ps1"; DestDir: "{app}"; Flags: ignoreversion
 Source: ".\assets\app.ico"; DestDir: "{app}"; Flags: ignoreversion
+#if DirExists("..\dist\windows-amd64\cuda")
+  Source: "..\dist\windows-amd64\cuda\*"; DestDir: "{app}\cuda\"; Flags: ignoreversion recursesubdirs
+#endif
+#if DirExists("..\dist\windows-amd64\oneapi")
+  Source: "..\dist\windows-amd64\oneapi\*"; DestDir: "{app}\oneapi\"; Flags: ignoreversion recursesubdirs
+#endif
+#if DirExists("..\dist\windows-amd64\rocm")
+  Source: "..\dist\windows-amd64\rocm\*"; DestDir: "{app}\rocm\"; Flags: ignoreversion recursesubdirs
+#endif
+
 
 [Icons]
 Name: "{group}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFilename: "{app}\app.ico"
@@ -108,9 +108,6 @@ Name: "{userstartup}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFilen
 Name: "{userprograms}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFilename: "{app}\app.ico"
 
 [Run]
-#if DirExists("..\dist\windows-arm64")
-Filename: "{tmp}\vc_redist.arm64.exe"; Parameters: "/install /passive /norestart"; Check: IsArm64() and vc_redist_needed(); StatusMsg: "Installing VC++ Redistributables..."; Flags: waituntilterminated
-#endif
 Filename: "{cmd}"; Parameters: "/C set PATH={app};%PATH% & ""{app}\{#MyAppExeName}"""; Flags: postinstall nowait runhidden
 
 [UninstallRun]
@@ -130,18 +127,14 @@ Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\models"
 Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\history"
 ; NOTE: if the user has a custom OLLAMA_MODELS it will be preserved
 
-[InstallDelete]
-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.
 
 
 ;FinishedHeadingLabel=Run your first model
-;FinishedLabel=%nRun this command in a PowerShell or cmd terminal.%n%n%n    ollama run llama3.2
+;FinishedLabel=%nRun this command in a PowerShell or cmd terminal.%n%n%n    ollama run llama3
 ;ClickFinish=%n
 
 [Registry]
@@ -166,39 +159,3 @@ begin
   { Pos() returns 0 if not found }
   Result := Pos(';' + ExpandConstant(Param) + ';', ';' + OrigPath + ';') = 0;
 end;
-
-{ --- VC Runtime libraries discovery code - Only install vc_redist if it isn't already installed ----- }
-const VCRTL_MIN_V1 = 14;
-const VCRTL_MIN_V2 = 40;
-const VCRTL_MIN_V3 = 33807;
-const VCRTL_MIN_V4 = 0;
-
- // check if the minimum required vc redist is installed (by looking the registry)
-function vc_redist_needed (): Boolean;
-var
-  sRegKey: string;
-  v1: Cardinal;
-  v2: Cardinal;
-  v3: Cardinal;
-  v4: Cardinal;
-begin
-  sRegKey := 'SOFTWARE\WOW6432Node\Microsoft\VisualStudio\14.0\VC\Runtimes\arm64';
-  if (RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'Major', v1)  and
-      RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'Minor', v2) and
-      RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'Bld', v3) and
-      RegQueryDWordValue (HKEY_LOCAL_MACHINE, sRegKey, 'RBld', v4)) then
-  begin
-    Log ('VC Redist version: ' + IntToStr (v1) +
-        '.' + IntToStr (v2) + '.' + IntToStr (v3) +
-        '.' + IntToStr (v4));
-    { Version info was found. Return true if later or equal to our
-       minimal required version RTL_MIN_Vx }
-    Result := not (
-        (v1 > VCRTL_MIN_V1) or ((v1 = VCRTL_MIN_V1) and
-         ((v2 > VCRTL_MIN_V2) or ((v2 = VCRTL_MIN_V2) and
-          ((v3 > VCRTL_MIN_V3) or ((v3 = VCRTL_MIN_V3) and
-           (v4 >= VCRTL_MIN_V4)))))));
-  end
-  else
-    Result := TRUE;
-end;

app/ollama_welcome.ps1

@@ -4,5 +4,5 @@ write-host "Welcome to Ollama!"
 write-host ""
 write-host "Run your first model:"
 write-host ""
-write-host "`tollama run llama3.2"
+write-host "`tollama run llama3"
 write-host ""

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/tray_nonwindows.go

@@ -3,11 +3,11 @@
 package tray
 
 import (
-	"errors"
+	"fmt"
 
 	"github.com/ollama/ollama/app/tray/commontray"
 )
 
 func InitPlatformTray(icon, updateIcon []byte) (commontray.OllamaTray, error) {
-	return nil, errors.New("not implemented")
+	return nil, fmt.Errorf("NOT IMPLEMENTED YET")
 }

app/tray/wintray/eventloop.go

@@ -11,7 +11,9 @@ import (
 	"golang.org/x/sys/windows"
 )
 
-var quitOnce sync.Once
+var (
+	quitOnce sync.Once
+)
 
 func (t *winTray) Run() {
 	nativeLoop()
@@ -98,7 +100,7 @@ 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
+	updatAvailableMenuID = 1
+	updateMenuID         = updatAvailableMenuID + 1
+	separatorMenuID      = updateMenuID + 1
+	diagLogsMenuID       = separatorMenuID + 1
+	diagSeparatorMenuID  = diagLogsMenuID + 1
+	quitMenuID           = diagSeparatorMenuID + 1
 )
 
 func (t *winTray) initMenus() error {
@@ -36,10 +35,10 @@ func (t *winTray) initMenus() error {
 func (t *winTray) UpdateAvailable(ver string) error {
 	if !t.updateNotified {
 		slog.Debug("updating menu and sending notification for new update")
-		if err := t.addOrUpdateMenuItem(updateAvailableMenuID, 0, updateAvailableMenuTitle, true); err != nil {
+		if err := t.addOrUpdateMenuItem(updatAvailableMenuID, 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

@@ -11,12 +11,10 @@ import (
 	"path/filepath"
 	"sort"
 	"sync"
-	"syscall"
 	"unsafe"
 
-	"golang.org/x/sys/windows"
-
 	"github.com/ollama/ollama/app/tray/commontray"
+	"golang.org/x/sys/windows"
 )
 
 // Helpful sources: https://github.com/golang/exp/blob/master/shiny/driver/internal/win32
@@ -361,7 +359,7 @@ 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,
@@ -416,7 +414,7 @@ func iconBytesToFilePath(iconBytes []byte) (string, error) {
 	iconFilePath := filepath.Join(os.TempDir(), "ollama_temp_icon_"+dataHash)
 
 	if _, err := os.Stat(iconFilePath); os.IsNotExist(err) {
-		if err := os.WriteFile(iconFilePath, iconBytes, 0o644); err != nil {
+		if err := os.WriteFile(iconFilePath, iconBytes, 0644); err != nil {
 			return "", err
 		}
 	}
@@ -434,12 +432,7 @@ func (t *winTray) setIcon(src string) error {
 	t.muNID.Lock()
 	defer t.muNID.Unlock()
 	t.nid.Icon = h
-	t.nid.Flags |= NIF_ICON | NIF_TIP
-	if toolTipUTF16, err := syscall.UTF16FromString(commontray.ToolTip); err == nil {
-		copy(t.nid.Tip[:], toolTipUTF16)
-	} else {
-		return err
-	}
+	t.nid.Flags |= NIF_ICON
 	t.nid.Size = uint32(unsafe.Sizeof(*t.nid))
 
 	return t.nid.modify()

app/tray/wintray/w32api.go

@@ -61,13 +61,11 @@ const (
 	MIIM_SUBMENU        = 0x00000004
 	MIM_APPLYTOSUBMENUS = 0x80000000
 	NIF_ICON            = 0x00000002
-	NIF_TIP             = 0x00000004
 	NIF_INFO            = 0x00000010
 	NIF_MESSAGE         = 0x00000001
 	SW_HIDE             = 0
 	TPM_BOTTOMALIGN     = 0x0020
 	TPM_LEFTALIGN       = 0x0000
-	TPM_RIGHTBUTTON     = 0x0002
 	WM_CLOSE            = 0x0010
 	WM_USER             = 0x0400
 	WS_CAPTION          = 0x00C00000

auth/auth.go

@@ -5,7 +5,6 @@ import (
 	"context"
 	"crypto/rand"
 	"encoding/base64"
-	"errors"
 	"fmt"
 	"io"
 	"log/slog"
@@ -79,7 +78,7 @@ func Sign(ctx context.Context, bts []byte) (string, error) {
 	publicKey := ssh.MarshalAuthorizedKey(privateKey.PublicKey())
 	parts := bytes.Split(publicKey, []byte(" "))
 	if len(parts) < 2 {
-		return "", errors.New("malformed public key")
+		return "", fmt.Errorf("malformed public key")
 	}
 
 	signedData, err := privateKey.Sign(rand.Reader, bts)

benchmark/server_benchmark_test.go

@@ -1,178 +0,0 @@
-package benchmark
-
-import (
-	"context"
-	"flag"
-	"fmt"
-	"testing"
-	"time"
-
-	"github.com/ollama/ollama/api"
-)
-
-// Command line flags
-var modelFlag string
-
-func init() {
-	flag.StringVar(&modelFlag, "m", "", "Name of the model to benchmark")
-	flag.Lookup("m").DefValue = "model"
-}
-
-// modelName returns the model name from flags, failing the test if not set
-func modelName(b *testing.B) string {
-	if modelFlag == "" {
-		b.Fatal("Error: -m flag is required for benchmark tests")
-	}
-	return modelFlag
-}
-
-type TestCase struct {
-	name      string
-	prompt    string
-	maxTokens int
-}
-
-// runGenerateBenchmark contains the common generate and metrics logic
-func runGenerateBenchmark(b *testing.B, ctx context.Context, client *api.Client, req *api.GenerateRequest) {
-	start := time.Now()
-	var ttft time.Duration
-	var metrics api.Metrics
-
-	err := client.Generate(ctx, req, func(resp api.GenerateResponse) error {
-		if ttft == 0 && resp.Response != "" {
-			ttft = time.Since(start)
-		}
-		if resp.Done {
-			metrics = resp.Metrics
-		}
-		return nil
-	})
-
-	// Report custom metrics as part of the benchmark results
-	b.ReportMetric(float64(ttft.Milliseconds()), "ttft_ms")
-	b.ReportMetric(float64(metrics.LoadDuration.Milliseconds()), "load_ms")
-
-	// Token throughput metrics
-	promptThroughput := float64(metrics.PromptEvalCount) / metrics.PromptEvalDuration.Seconds()
-	genThroughput := float64(metrics.EvalCount) / metrics.EvalDuration.Seconds()
-	b.ReportMetric(promptThroughput, "prompt_tok/s")
-	b.ReportMetric(genThroughput, "gen_tok/s")
-
-	// Token counts
-	b.ReportMetric(float64(metrics.PromptEvalCount), "prompt_tokens")
-	b.ReportMetric(float64(metrics.EvalCount), "gen_tokens")
-	if err != nil {
-		b.Fatal(err)
-	}
-}
-
-// BenchmarkColdStart runs benchmarks with model loading from cold state
-func BenchmarkColdStart(b *testing.B) {
-	client := setup(b)
-	tests := []TestCase{
-		{"short_prompt", "Write a long story", 100},
-		{"medium_prompt", "Write a detailed economic analysis", 500},
-		{"long_prompt", "Write a comprehensive AI research paper", 1000},
-	}
-	m := modelName(b)
-
-	for _, tt := range tests {
-		b.Run(fmt.Sprintf("%s/cold/%s", m, tt.name), func(b *testing.B) {
-			ctx := context.Background()
-
-			// Set number of tokens as our throughput metric
-			b.SetBytes(int64(tt.maxTokens))
-
-			for b.Loop() {
-				b.StopTimer()
-				// Ensure model is unloaded before each iteration
-				unload(client, m, b)
-				b.StartTimer()
-
-				req := &api.GenerateRequest{
-					Model:   m,
-					Prompt:  tt.prompt,
-					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
-				}
-
-				runGenerateBenchmark(b, ctx, client, req)
-			}
-		})
-	}
-}
-
-// BenchmarkWarmStart runs benchmarks with pre-loaded model
-func BenchmarkWarmStart(b *testing.B) {
-	client := setup(b)
-	tests := []TestCase{
-		{"short_prompt", "Write a long story", 100},
-		{"medium_prompt", "Write a detailed economic analysis", 500},
-		{"long_prompt", "Write a comprehensive AI research paper", 1000},
-	}
-	m := modelName(b)
-
-	for _, tt := range tests {
-		b.Run(fmt.Sprintf("%s/warm/%s", m, tt.name), func(b *testing.B) {
-			ctx := context.Background()
-
-			// Pre-warm the model
-			warmup(client, m, tt.prompt, b)
-
-			// Set number of tokens as our throughput metric
-			b.SetBytes(int64(tt.maxTokens))
-
-			for b.Loop() {
-				req := &api.GenerateRequest{
-					Model:   m,
-					Prompt:  tt.prompt,
-					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
-				}
-
-				runGenerateBenchmark(b, ctx, client, req)
-			}
-		})
-	}
-}
-
-// setup verifies server and model availability
-func setup(b *testing.B) *api.Client {
-	client, err := api.ClientFromEnvironment()
-	if err != nil {
-		b.Fatal(err)
-	}
-	if _, err := client.Show(context.Background(), &api.ShowRequest{Model: modelName(b)}); err != nil {
-		b.Fatalf("Model unavailable: %v", err)
-	}
-
-	return client
-}
-
-// warmup ensures the model is loaded and warmed up
-func warmup(client *api.Client, model string, prompt string, b *testing.B) {
-	for range 3 {
-		err := client.Generate(
-			context.Background(),
-			&api.GenerateRequest{
-				Model:   model,
-				Prompt:  prompt,
-				Options: map[string]any{"num_predict": 50, "temperature": 0.1},
-			},
-			func(api.GenerateResponse) error { return nil },
-		)
-		if err != nil {
-			b.Logf("Error during model warm-up: %v", err)
-		}
-	}
-}
-
-// unload forces model unloading using KeepAlive: 0 parameter
-func unload(client *api.Client, model string, b *testing.B) {
-	req := &api.GenerateRequest{
-		Model:     model,
-		KeepAlive: &api.Duration{Duration: 0},
-	}
-	if err := client.Generate(context.Background(), req, func(api.GenerateResponse) error { return nil }); err != nil {
-		b.Logf("Unload error: %v", err)
-	}
-	time.Sleep(1 * time.Second)
-}

cmd/cmd_test.go

@@ -1,921 +0,0 @@
-package cmd
-
-import (
-	"bytes"
-	"context"
-	"encoding/json"
-	"io"
-	"net/http"
-	"net/http/httptest"
-	"os"
-	"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) {
-	t.Run("bare details", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture    test    
-    parameters      7B      
-    quantization    FP16    
-
-`
-
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			t.Errorf("unexpected output (-want +got):\n%s", diff)
-		}
-	})
-
-	t.Run("bare model info", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			ModelInfo: map[string]any{
-				"general.architecture":    "test",
-				"general.parameter_count": float64(7_000_000_000),
-				"test.context_length":     float64(0),
-				"test.embedding_length":   float64(0),
-			},
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture        test    
-    parameters          7B      
-    context length      0       
-    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)
-		}
-	})
-
-	t.Run("parameters", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-			Parameters: `
-			stop never
-			stop gonna
-			stop give
-			stop you
-			stop up
-			temperature 99`,
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture    test    
-    parameters      7B      
-    quantization    FP16    
-
-  Parameters
-    stop           never    
-    stop           gonna    
-    stop           give     
-    stop           you      
-    stop           up       
-    temperature    99       
-
-`
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			t.Errorf("unexpected output (-want +got):\n%s", diff)
-		}
-	})
-
-	t.Run("project info", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-			ProjectorInfo: map[string]any{
-				"general.architecture":         "clip",
-				"general.parameter_count":      float64(133_700_000),
-				"clip.vision.embedding_length": float64(0),
-				"clip.vision.projection_dim":   float64(0),
-			},
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture    test    
-    parameters      7B      
-    quantization    FP16    
-
-  Projector
-    architecture        clip       
-    parameters          133.70M    
-    embedding length    0          
-    dimensions          0          
-
-`
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			t.Errorf("unexpected output (-want +got):\n%s", diff)
-		}
-	})
-
-	t.Run("system", func(t *testing.T) {
-		var b bytes.Buffer
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-			System: `You are a pirate!
-Ahoy, matey!
-Weigh anchor!
-			`,
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture    test    
-    parameters      7B      
-    quantization    FP16    
-
-  System
-    You are a pirate!    
-    Ahoy, matey!         
-
-`
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			t.Errorf("unexpected output (-want +got):\n%s", diff)
-		}
-	})
-
-	t.Run("license", func(t *testing.T) {
-		var b bytes.Buffer
-		license := "MIT License\nCopyright (c) Ollama\n"
-		if err := showInfo(&api.ShowResponse{
-			Details: api.ModelDetails{
-				Family:            "test",
-				ParameterSize:     "7B",
-				QuantizationLevel: "FP16",
-			},
-			License: license,
-		}, false, &b); err != nil {
-			t.Fatal(err)
-		}
-
-		expect := `  Model
-    architecture    test    
-    parameters      7B      
-    quantization    FP16    
-
-  License
-    MIT License             
-    Copyright (c) Ollama    
-
-`
-		if diff := cmp.Diff(expect, b.String()); diff != "" {
-			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) {
-	stopped := false
-	mockServer := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-		if r.URL.Path == "/api/delete" && r.Method == http.MethodDelete {
-			var req api.DeleteRequest
-			if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
-				http.Error(w, err.Error(), http.StatusBadRequest)
-				return
-			}
-			if req.Name == "test-model" {
-				w.WriteHeader(http.StatusOK)
-			} else {
-				w.WriteHeader(http.StatusNotFound)
-			}
-			return
-		}
-		if r.URL.Path == "/api/generate" && r.Method == http.MethodPost {
-			var req api.GenerateRequest
-			if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
-				http.Error(w, err.Error(), http.StatusBadRequest)
-				return
-			}
-			if req.Model == "test-model" {
-				w.WriteHeader(http.StatusOK)
-				if err := json.NewEncoder(w).Encode(api.GenerateResponse{
-					Done: true,
-				}); err != nil {
-					http.Error(w, err.Error(), http.StatusInternalServerError)
-				}
-				stopped = true
-				return
-			} else {
-				w.WriteHeader(http.StatusNotFound)
-				if err := json.NewEncoder(w).Encode(api.GenerateResponse{
-					Done: false,
-				}); err != nil {
-					http.Error(w, err.Error(), http.StatusInternalServerError)
-				}
-			}
-		}
-	}))
-
-	t.Setenv("OLLAMA_HOST", mockServer.URL)
-	t.Cleanup(mockServer.Close)
-
-	cmd := &cobra.Command{}
-	cmd.SetContext(context.TODO())
-	if err := DeleteHandler(cmd, []string{"test-model"}); err != nil {
-		t.Fatalf("DeleteHandler failed: %v", err)
-	}
-	if !stopped {
-		t.Fatal("Model was not stopped before deletion")
-	}
-
-	err := DeleteHandler(cmd, []string{"test-model-not-found"})
-	if err == nil || !strings.Contains(err.Error(), "unable to stop existing running model \"test-model-not-found\"") {
-		t.Fatalf("DeleteHandler failed: expected error about stopping non-existent model, got %v", err)
-	}
-}
-
-func TestGetModelfileName(t *testing.T) {
-	tests := []struct {
-		name          string
-		modelfileName string
-		fileExists    bool
-		expectedName  string
-		expectedErr   error
-	}{
-		{
-			name:          "no modelfile specified, no modelfile exists",
-			modelfileName: "",
-			fileExists:    false,
-			expectedName:  "",
-			expectedErr:   os.ErrNotExist,
-		},
-		{
-			name:          "no modelfile specified, modelfile exists",
-			modelfileName: "",
-			fileExists:    true,
-			expectedName:  "Modelfile",
-			expectedErr:   nil,
-		},
-		{
-			name:          "modelfile specified, no modelfile exists",
-			modelfileName: "crazyfile",
-			fileExists:    false,
-			expectedName:  "",
-			expectedErr:   os.ErrNotExist,
-		},
-		{
-			name:          "modelfile specified, modelfile exists",
-			modelfileName: "anotherfile",
-			fileExists:    true,
-			expectedName:  "anotherfile",
-			expectedErr:   nil,
-		},
-	}
-
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			cmd := &cobra.Command{
-				Use: "fakecmd",
-			}
-			cmd.Flags().String("file", "", "path to modelfile")
-
-			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
-				} else {
-					fn = "Modelfile"
-				}
-
-				tempFile, err := os.CreateTemp(tempDir, fn)
-				if err != nil {
-					t.Fatalf("temp modelfile creation failed: %v", err)
-				}
-
-				expectedFilename = tempFile.Name()
-				err = cmd.Flags().Set("file", expectedFilename)
-				if err != nil {
-					t.Fatalf("couldn't set file flag: %v", err)
-				}
-			} else {
-				expectedFilename = tt.expectedName
-				if tt.modelfileName != "" {
-					err := cmd.Flags().Set("file", tt.modelfileName)
-					if err != nil {
-						t.Fatalf("couldn't set file flag: %v", err)
-					}
-				}
-			}
-
-			actualFilename, actualErr := getModelfileName(cmd)
-
-			if actualFilename != expectedFilename {
-				t.Errorf("expected filename: '%s' actual filename: '%s'", expectedFilename, actualFilename)
-			}
-
-			if tt.expectedErr != os.ErrNotExist {
-				if actualErr != tt.expectedErr {
-					t.Errorf("expected err: %v actual err: %v", tt.expectedErr, actualErr)
-				}
-			} else {
-				if !os.IsNotExist(actualErr) {
-					t.Errorf("expected err: %v actual err: %v", tt.expectedErr, actualErr)
-				}
-			}
-		})
-	}
-}
-
-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(context.TODO())
-
-			// 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(context.TODO())
-
-			// 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.Name != "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("", "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(context.TODO())
-
-			// 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

@@ -1,7 +1,6 @@
 package cmd
 
 import (
-	"cmp"
 	"errors"
 	"fmt"
 	"io"
@@ -10,15 +9,16 @@ import (
 	"path/filepath"
 	"regexp"
 	"slices"
+	"sort"
 	"strings"
 
 	"github.com/spf13/cobra"
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/envconfig"
+	"github.com/ollama/ollama/progress"
 	"github.com/ollama/ollama/readline"
 	"github.com/ollama/ollama/types/errtypes"
-	"github.com/ollama/ollama/types/model"
 )
 
 type MultilineState int
@@ -27,9 +27,49 @@ const (
 	MultilineNone MultilineState = iota
 	MultilinePrompt
 	MultilineSystem
+	MultilineTemplate
 )
 
+func loadModel(cmd *cobra.Command, opts *runOptions) error {
+	p := progress.NewProgress(os.Stderr)
+	defer p.StopAndClear()
+
+	spinner := progress.NewSpinner("")
+	p.Add("", spinner)
+
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		return err
+	}
+
+	chatReq := &api.ChatRequest{
+		Model:     opts.Model,
+		KeepAlive: opts.KeepAlive,
+	}
+
+	return client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
+		p.StopAndClear()
+		for _, msg := range opts.Messages {
+			switch msg.Role {
+			case "user":
+				fmt.Printf(">>> %s\n", msg.Content)
+			case "assistant":
+				state := &displayResponseState{}
+				displayResponse(msg.Content, opts.WordWrap, state)
+				fmt.Println()
+				fmt.Println()
+			}
+		}
+		return nil
+	})
+}
+
 func generateInteractive(cmd *cobra.Command, opts runOptions) error {
+	err := loadModel(cmd, &opts)
+	if err != nil {
+		return err
+	}
+
 	usage := func() {
 		fmt.Fprintln(os.Stderr, "Available Commands:")
 		fmt.Fprintln(os.Stderr, "  /set            Set session variables")
@@ -54,6 +94,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "Available Commands:")
 		fmt.Fprintln(os.Stderr, "  /set parameter ...     Set a parameter")
 		fmt.Fprintln(os.Stderr, "  /set system <string>   Set system message")
+		fmt.Fprintln(os.Stderr, "  /set template <string> Set prompt template")
 		fmt.Fprintln(os.Stderr, "  /set history           Enable history")
 		fmt.Fprintln(os.Stderr, "  /set nohistory         Disable history")
 		fmt.Fprintln(os.Stderr, "  /set wordwrap          Enable wordwrap")
@@ -99,7 +140,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		fmt.Fprintln(os.Stderr, "  /set parameter num_predict <int>      Max number of tokens to predict")
 		fmt.Fprintln(os.Stderr, "  /set parameter top_k <int>            Pick from top k num of tokens")
 		fmt.Fprintln(os.Stderr, "  /set parameter top_p <float>          Pick token based on sum of probabilities")
-		fmt.Fprintln(os.Stderr, "  /set parameter min_p <float>          Pick token based on top token probability * min_p")
 		fmt.Fprintln(os.Stderr, "  /set parameter num_ctx <int>          Set the context size")
 		fmt.Fprintln(os.Stderr, "  /set parameter temperature <float>    Set creativity level")
 		fmt.Fprintln(os.Stderr, "  /set parameter repeat_penalty <float> How strongly to penalize repetitions")
@@ -119,7 +159,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 		return err
 	}
 
-	if envconfig.NoHistory() {
+	if envconfig.NoHistory {
 		scanner.HistoryDisable()
 	}
 
@@ -164,6 +204,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 				opts.Messages = append(opts.Messages, api.Message{Role: "system", Content: opts.System})
 				fmt.Println("Set system message.")
 				sb.Reset()
+			case MultilineTemplate:
+				opts.Template = sb.String()
+				fmt.Println("Set prompt template.")
+				sb.Reset()
 			}
 
 			multiline = MultilineNone
@@ -195,11 +239,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 			opts.Model = args[1]
 			opts.Messages = []api.Message{}
 			fmt.Printf("Loading model '%s'\n", opts.Model)
-			if err := loadOrUnloadModel(cmd, &opts); err != nil {
-				if strings.Contains(err.Error(), "not found") {
-					fmt.Printf("error: %v\n", err)
-					continue
-				}
+			if err := loadModel(cmd, &opts); err != nil {
 				return err
 			}
 			continue
@@ -216,7 +256,10 @@ 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 {
@@ -283,13 +326,17 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 					}
 					fmt.Printf("Set parameter '%s' to '%s'\n", args[2], strings.Join(params, ", "))
 					opts.Options[args[2]] = fp[args[2]]
-				case "system":
+				case "system", "template":
 					if len(args) < 3 {
 						usageSet()
 						continue
 					}
 
-					multiline = MultilineSystem
+					if args[1] == "system" {
+						multiline = MultilineSystem
+					} else if args[1] == "template" {
+						multiline = MultilineTemplate
+					}
 
 					line := strings.Join(args[2:], " ")
 					line, ok := strings.CutPrefix(line, `"""`)
@@ -309,16 +356,24 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 						continue
 					}
 
-					opts.System = sb.String() // for display in modelfile
-					newMessage := api.Message{Role: "system", Content: sb.String()}
-					// Check if the slice is not empty and the last message is from 'system'
-					if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
-						// Replace the last message
-						opts.Messages[len(opts.Messages)-1] = newMessage
-					} else {
-						opts.Messages = append(opts.Messages, newMessage)
+					if args[1] == "system" {
+						opts.System = sb.String() // for display in modelfile
+						newMessage := api.Message{Role: "system", Content: sb.String()}
+						// Check if the slice is not empty and the last message is from 'system'
+						if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
+							// Replace the last message
+							opts.Messages[len(opts.Messages)-1] = newMessage
+						} else {
+							opts.Messages = append(opts.Messages, newMessage)
+						}
+						fmt.Println("Set system message.")
+						sb.Reset()
+					} else if args[1] == "template" {
+						opts.Template = sb.String()
+						fmt.Println("Set prompt template.")
+						sb.Reset()
 					}
-					fmt.Println("Set system message.")
+
 					sb.Reset()
 					continue
 				default:
@@ -336,9 +391,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 					return err
 				}
 				req := &api.ShowRequest{
-					Name:    opts.Model,
-					System:  opts.System,
-					Options: opts.Options,
+					Name:     opts.Model,
+					System:   opts.System,
+					Template: opts.Template,
+					Options:  opts.Options,
 				}
 				resp, err := client.Show(cmd.Context(), req)
 				if err != nil {
@@ -348,7 +404,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 
 				switch args[1] {
 				case "info":
-					_ = showInfo(resp, false, os.Stderr)
+					showInfo(resp)
 				case "license":
 					if resp.License == "" {
 						fmt.Println("No license was specified for this model.")
@@ -381,9 +437,12 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 						fmt.Println("No system message was specified for this model.")
 					}
 				case "template":
-					if resp.Template != "" {
+					switch {
+					case opts.Template != "":
+						fmt.Println(opts.Template + "\n")
+					case resp.Template != "":
 						fmt.Println(resp.Template)
-					} else {
+					default:
 						fmt.Println("No prompt template was specified for this model.")
 					}
 				default:
@@ -440,6 +499,13 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 					return err
 				}
 
+				// clear all previous images for better responses
+				if len(images) > 0 {
+					for i := range opts.Messages {
+						opts.Messages[i].Images = nil
+					}
+				}
+
 				newMessage.Content = msg
 				newMessage.Images = images
 			}
@@ -459,58 +525,68 @@ 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 = ""
+func buildModelfile(opts runOptions) string {
+	var mf strings.Builder
+	model := opts.ParentModel
+	if model == "" {
+		model = opts.Model
 	}
-
-	req := &api.CreateRequest{
-		Model: name,
-		From:  cmp.Or(parentModel, opts.Model),
-	}
-
+	fmt.Fprintf(&mf, "FROM %s\n", model)
 	if opts.System != "" {
-		req.System = opts.System
+		fmt.Fprintf(&mf, "SYSTEM \"\"\"%s\"\"\"\n", opts.System)
 	}
 
-	if len(opts.Options) > 0 {
-		req.Parameters = opts.Options
+	if opts.Template != "" {
+		fmt.Fprintf(&mf, "TEMPLATE \"\"\"%s\"\"\"\n", opts.Template)
 	}
 
-	if len(opts.Messages) > 0 {
-		req.Messages = opts.Messages
+	keys := make([]string, 0)
+	for k := range opts.Options {
+		keys = append(keys, k)
+	}
+	sort.Strings(keys)
+	for _, k := range keys {
+		fmt.Fprintf(&mf, "PARAMETER %s %v\n", k, opts.Options[k])
+	}
+	fmt.Fprintln(&mf)
+
+	for _, msg := range opts.Messages {
+		fmt.Fprintf(&mf, "MESSAGE %s \"\"\"%s\"\"\"\n", msg.Role, msg.Content)
 	}
 
-	return req
+	return mf.String()
 }
 
 func normalizeFilePath(fp string) string {
-	return strings.NewReplacer(
-		"\\ ", " ", // Escaped space
-		"\\(", "(", // Escaped left parenthesis
-		"\\)", ")", // Escaped right parenthesis
-		"\\[", "[", // Escaped left square bracket
-		"\\]", "]", // Escaped right square bracket
-		"\\{", "{", // Escaped left curly brace
-		"\\}", "}", // Escaped right curly brace
-		"\\$", "$", // Escaped dollar sign
-		"\\&", "&", // Escaped ampersand
-		"\\;", ";", // Escaped semicolon
-		"\\'", "'", // Escaped single quote
-		"\\\\", "\\", // Escaped backslash
-		"\\*", "*", // Escaped asterisk
-		"\\?", "?", // Escaped question mark
-	).Replace(fp)
+	// Define a map of escaped characters and their replacements
+	replacements := map[string]string{
+		"\\ ":  " ",  // Escaped space
+		"\\(":  "(",  // Escaped left parenthesis
+		"\\)":  ")",  // Escaped right parenthesis
+		"\\[":  "[",  // Escaped left square bracket
+		"\\]":  "]",  // Escaped right square bracket
+		"\\{":  "{",  // Escaped left curly brace
+		"\\}":  "}",  // Escaped right curly brace
+		"\\$":  "$",  // Escaped dollar sign
+		"\\&":  "&",  // Escaped ampersand
+		"\\;":  ";",  // Escaped semicolon
+		"\\'":  "'",  // Escaped single quote
+		"\\\\": "\\", // Escaped backslash
+		"\\*":  "*",  // Escaped asterisk
+		"\\?":  "?",  // Escaped question mark
+	}
+
+	for escaped, actual := range replacements {
+		fp = strings.ReplaceAll(fp, escaped, actual)
+	}
+	return fp
 }
 
 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)\b`
+	regexPattern := `(?:[a-zA-Z]:)?(?:\./|/|\\)[\S\\ ]+?\.(?i:jpg|jpeg|png|svg)\b`
 	re := regexp.MustCompile(regexPattern)
 
 	return re.FindAllString(input, -1)
@@ -523,9 +599,10 @@ func extractFileData(input string) (string, []api.ImageData, error) {
 	for _, fp := range filePaths {
 		nfp := normalizeFilePath(fp)
 		data, err := getImageData(nfp)
-		if errors.Is(err, os.ErrNotExist) {
-			continue
-		} else if err != nil {
+		if err != nil {
+			if os.IsNotExist(err) {
+				continue
+			}
 			fmt.Fprintf(os.Stderr, "Couldn't process image: %q\n", err)
 			return "", imgs, err
 		}
@@ -533,7 +610,7 @@ func extractFileData(input string) (string, []api.ImageData, error) {
 		input = strings.ReplaceAll(input, fp, "")
 		imgs = append(imgs, data)
 	}
-	return strings.TrimSpace(input), imgs, nil
+	return input, imgs, nil
 }
 
 func getImageData(filePath string) ([]byte, error) {
@@ -563,7 +640,7 @@ func getImageData(filePath string) ([]byte, error) {
 	// Check if the file size exceeds 100MB
 	var maxSize int64 = 100 * 1024 * 1024 // 100MB in bytes
 	if info.Size() > maxSize {
-		return nil, errors.New("file size exceeds maximum limit (100MB)")
+		return nil, fmt.Errorf("file size exceeds maximum limit (100MB)")
 	}
 
 	buf = make([]byte, info.Size())

cmd/interactive_test.go

@@ -1,52 +1,117 @@
 package cmd
 
 import (
+	"bytes"
 	"testing"
+	"text/template"
 
 	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/require"
+
+	"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`
+ ./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, 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[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 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, 10)
-	assert.NotContains(t, res, "inbetween2")
+	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:")
 }
+
+func TestModelfileBuilder(t *testing.T) {
+	opts := runOptions{
+		Model:    "hork",
+		System:   "You are part horse and part shark, but all hork. Do horklike things",
+		Template: "This is a template.",
+		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]interface{}{},
+	}
+
+	opts.Options["temperature"] = 0.9
+	opts.Options["seed"] = 42
+	opts.Options["penalize_newline"] = false
+	opts.Options["stop"] = []string{"hi", "there"}
+
+	mf := buildModelfile(opts)
+	expectedModelfile := `FROM {{.Model}}
+SYSTEM """{{.System}}"""
+TEMPLATE """{{.Template}}"""
+PARAMETER penalize_newline false
+PARAMETER seed 42
+PARAMETER stop [hi there]
+PARAMETER temperature 0.9
+
+MESSAGE user """Hey there hork!"""
+MESSAGE assistant """Yes it is true, I am half horse, half shark."""
+`
+
+	tmpl, err := template.New("").Parse(expectedModelfile)
+	require.NoError(t, err)
+
+	var buf bytes.Buffer
+	err = tmpl.Execute(&buf, opts)
+	require.NoError(t, err)
+	assert.Equal(t, buf.String(), mf)
+
+	opts.ParentModel = "horseshark"
+	mf = buildModelfile(opts)
+	expectedModelfile = `FROM {{.ParentModel}}
+SYSTEM """{{.System}}"""
+TEMPLATE """{{.Template}}"""
+PARAMETER penalize_newline false
+PARAMETER seed 42
+PARAMETER stop [hi there]
+PARAMETER temperature 0.9
+
+MESSAGE user """Hey there hork!"""
+MESSAGE assistant """Yes it is true, I am half horse, half shark."""
+`
+
+	tmpl, err = template.New("").Parse(expectedModelfile)
+	require.NoError(t, err)
+
+	var parentBuf bytes.Buffer
+	err = tmpl.Execute(&parentBuf, opts)
+	require.NoError(t, err)
+	assert.Equal(t, parentBuf.String(), mf)
+}

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

@@ -2,7 +2,7 @@ package cmd
 
 import (
 	"context"
-	"errors"
+	"fmt"
 	"os"
 	"os/exec"
 	"strings"
@@ -20,7 +20,7 @@ func startApp(ctx context.Context, client *api.Client) error {
 		return err
 	}
 	if !strings.Contains(link, "Ollama.app") {
-		return errors.New("could not find ollama app")
+		return fmt.Errorf("could not find ollama app")
 	}
 	path := strings.Split(link, "Ollama.app")
 	if err := exec.Command("/usr/bin/open", "-a", path[0]+"Ollama.app").Run(); err != nil {

cmd/start_default.go

@@ -4,11 +4,11 @@ package cmd
 
 import (
 	"context"
-	"errors"
+	"fmt"
 
 	"github.com/ollama/ollama/api"
 )
 
 func startApp(ctx context.Context, client *api.Client) error {
-	return errors.New("could not connect to ollama server, run 'ollama serve' to start it")
+	return fmt.Errorf("could not connect to ollama server, run 'ollama serve' to start it")
 }

cmd/start_windows.go

@@ -31,7 +31,7 @@ func startApp(ctx context.Context, client *api.Client) error {
 			// Finally look in the path
 			appExe, err = exec.LookPath(AppName)
 			if err != nil {
-				return errors.New("could not locate ollama app")
+				return fmt.Errorf("could not locate ollama app")
 			}
 		}
 	}

convert/convert.go

@@ -5,35 +5,20 @@ import (
 	"errors"
 	"fmt"
 	"io"
-	"io/fs"
 	"log/slog"
-	"strings"
+	"os"
+	"path/filepath"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/llm"
 )
 
-type ModelParameters struct {
-	Architectures []string       `json:"architectures"`
-	VocabSize     uint32         `json:"vocab_size"`
-	TextModel     TextParameters `json:"text_config"`
+type Parameters struct {
+	Architectures []string `json:"architectures"`
+	VocabSize     uint32   `json:"vocab_size"`
 }
 
-type TextParameters struct {
-	VocabSize uint32 `json:"vocab_size"`
-}
-
-type AdapterParameters struct {
-	Alpha          uint32 `json:"lora_alpha"`
-	LoraLayers     uint32 `json:"lora_layers"`
-	LoraParameters struct {
-		Rank  uint32  `json:"rank"`
-		Alpha float32 `json:"alpha"`
-		Scale float32 `json:"scale"`
-	} `json:"lora_parameters"`
-}
-
-func (ModelParameters) KV(t *Tokenizer) ggml.KV {
-	kv := ggml.KV{
+func (Parameters) KV(t *Tokenizer) llm.KV {
+	kv := llm.KV{
 		"general.file_type":            uint32(1),
 		"general.quantization_version": uint32(2),
 		"tokenizer.ggml.pre":           t.Pre,
@@ -43,10 +28,6 @@ func (ModelParameters) KV(t *Tokenizer) ggml.KV {
 		"tokenizer.ggml.token_type":    t.Vocabulary.Types,
 	}
 
-	if len(t.Merges) > 0 {
-		kv["tokenizer.ggml.merges"] = t.Merges
-	}
-
 	if t.Template != "" {
 		kv["tokenizer.chat_template"] = t.Template
 	}
@@ -59,120 +40,49 @@ func (ModelParameters) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p AdapterParameters) KV() ggml.KV {
-	var alpha float32
-	if p.LoraParameters.Alpha == 0 {
-		alpha = float32(p.Alpha)
-	} else {
-		alpha = p.LoraParameters.Alpha
-	}
-
-	kv := ggml.KV{
-		"adapter.lora.alpha": alpha,
-		"adapter.type":       "lora",
-		"general.file_type":  uint32(1),
-		"general.type":       "adapter",
-		"general.version":    "v0.2",
-	}
-
-	return kv
-}
-
-func (ModelParameters) specialTokenTypes() []string {
+func (Parameters) specialTypes() []string {
 	return []string{
 		"bos", "eos", "unk", "sep", "pad", "cls", "mask",
 	}
 }
 
-func (ModelParameters) writeFile(ws io.WriteSeeker, kv ggml.KV, ts []ggml.Tensor) error {
-	return ggml.WriteGGUF(ws, kv, ts)
+func (Parameters) writeFile(ws io.WriteSeeker, kv llm.KV, ts []*llm.Tensor) error {
+	return llm.WriteGGUF(ws, kv, ts)
 }
 
-func (AdapterParameters) writeFile(ws io.WriteSeeker, kv ggml.KV, ts []ggml.Tensor) error {
-	return ggml.WriteGGUF(ws, kv, ts)
-}
-
-type ModelConverter interface {
+type Converter interface {
 	// KV maps parameters to LLM key-values
-	KV(*Tokenizer) ggml.KV
+	KV(*Tokenizer) llm.KV
 	// Tensors maps input tensors to LLM tensors. Model specific modifications can be done here.
-	Tensors([]Tensor) []ggml.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
+	Tensors([]Tensor) []*llm.Tensor
 
-	// specialTokenTypes returns any special token types the model uses
-	specialTokenTypes() []string
-	// writeFile writes the model to the provided io.WriteSeeker
-	writeFile(io.WriteSeeker, ggml.KV, []ggml.Tensor) error
+	// tensorName returns the LLM tensor name for a specific input name
+	tensorName(string) string
+	// specialTypes returns any special token types the model uses
+	specialTypes() []string
+	writeFile(io.WriteSeeker, llm.KV, []*llm.Tensor) error
 }
 
-type moreParser interface {
-	parseMore(fs.FS) error
-}
+func ConvertAdapter(d string, ws io.WriteSeeker) error {
+	c := &adapter{}
 
-type AdapterConverter interface {
-	// KV maps parameters to LLM key-values
-	KV(ggml.KV) ggml.KV
-	// Tensors maps input tensors to LLM tensors. Adapter specific modifications can be done here.
-	Tensors([]Tensor) []ggml.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, ggml.KV, []ggml.Tensor) error
-}
-
-func ConvertAdapter(fsys fs.FS, ws io.WriteSeeker, baseKV ggml.KV) error {
-	bts, err := fs.ReadFile(fsys, "adapter_config.json")
+	ts, err := parseNPZ(d)
 	if err != nil {
 		return err
 	}
 
-	var p AdapterParameters
-	if err := json.Unmarshal(bts, &p); err != nil {
-		return err
-	}
-
-	arch, ok := baseKV["general.architecture"]
-	if !ok {
-		return errors.New("architecture not set for the base model")
-	}
-
-	var conv AdapterConverter
-	switch arch {
-	case "llama":
-		conv = &llamaAdapter{}
-	case "gemma2":
-		conv = &gemma2Adapter{}
-	default:
-		return errors.New("unsupported architecture")
-	}
-
-	ts, err := parseTensors(fsys, strings.NewReplacer(conv.Replacements()...))
-	if err != nil {
-		return err
-	}
-
-	if err := json.Unmarshal(bts, conv); err != nil {
-		return err
-	}
-
-	return conv.writeFile(ws, conv.KV(baseKV), conv.Tensors(ts))
+	return c.writeFile(ws, c.KV(nil), c.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, ws io.WriteSeeker) error {
-	bts, err := fs.ReadFile(fsys, "config.json")
+func Convert(d string, ws io.WriteSeeker) error {
+	f, err := os.Open(filepath.Join(d, "config.json"))
 	if err != nil {
 		return err
 	}
+	defer f.Close()
 
-	var p ModelParameters
-	if err := json.Unmarshal(bts, &p); err != nil {
+	var p Parameters
+	if err := json.NewDecoder(f).Decode(&p); err != nil {
 		return err
 	}
 
@@ -180,73 +90,45 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 		return errors.New("unknown architecture")
 	}
 
-	var conv ModelConverter
+	var c Converter
 	switch p.Architectures[0] {
-	case "LlamaForCausalLM":
-		conv = &llamaModel{}
-	case "Mistral3ForConditionalGeneration":
-		conv = &mistral3Model{}
+	case "LlamaForCausalLM", "MistralForCausalLM":
+		c = &llama{}
 	case "MixtralForCausalLM":
-		conv = &mixtralModel{}
+		c = &mixtral{}
 	case "GemmaForCausalLM":
-		conv = &gemmaModel{}
-	case "Gemma2ForCausalLM":
-		conv = &gemma2Model{}
-	case "Gemma3ForCausalLM", "Gemma3ForConditionalGeneration":
-		conv = &gemma3Model{Architecture: p.Architectures[0]}
-	case "Phi3ForCausalLM":
-		conv = &phi3Model{}
-	case "Qwen2ForCausalLM":
-		conv = &qwen2Model{}
-	case "BertModel":
-		conv = &bertModel{}
-	case "CohereForCausalLM":
-		conv = &commandrModel{}
+		c = &gemma{}
 	default:
-		return fmt.Errorf("unsupported architecture %q", p.Architectures[0])
+		return errors.New("unsupported architecture")
 	}
 
-	if err := json.Unmarshal(bts, conv); err != nil {
-		return err
-	}
-
-	if t, ok := conv.(moreParser); ok {
-		if err := t.parseMore(fsys); err != nil {
-			return err
-		}
-	}
-
-	t, err := parseTokenizer(fsys, conv.specialTokenTypes())
+	bts, err := os.ReadFile(filepath.Join(d, "config.json"))
 	if err != nil {
 		return err
 	}
 
-	vocabSize := int(p.VocabSize)
-	if vocabSize == 0 {
-		tVocabSize := int(p.TextModel.VocabSize)
-		vocabSize = tVocabSize
+	if err := json.Unmarshal(bts, c); err != nil {
+		return err
 	}
 
-	switch {
-	case vocabSize == 0:
-		slog.Warn("vocabulary size was not explicitly set by the model", "default size", len(t.Vocabulary.Tokens))
-	case vocabSize > len(t.Vocabulary.Tokens):
-		slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
+	t, err := parseTokenizer(d, c.specialTypes())
+	if err != nil {
+		return err
+	}
+
+	if vocabSize := int(p.VocabSize); vocabSize > len(t.Vocabulary.Tokens) {
+		slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", p.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):
-		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))
 	}
 
-	ts, err := parseTensors(fsys, strings.NewReplacer(conv.Replacements()...))
+	ts, err := parseTensors(d)
 	if err != nil {
 		return err
 	}
 
-	return conv.writeFile(ws, conv.KV(t), conv.Tensors(ts))
+	return c.writeFile(ws, c.KV(t), c.Tensors(ts))
 }

convert/convert_adapter.go

@@ -0,0 +1,56 @@
+package convert
+
+import (
+	"io"
+	"strings"
+
+	"github.com/ollama/ollama/llm"
+)
+
+type adapter struct {
+	Parameters
+}
+
+var _ Converter = (*adapter)(nil)
+
+func (p *adapter) writeFile(ws io.WriteSeeker, kv llm.KV, ts []*llm.Tensor) error {
+	return llm.WriteGGLA(ws, kv, ts)
+}
+
+func (p *adapter) KV(t *Tokenizer) llm.KV {
+	// todo - need a way to pass these in
+	kv := llm.KV{
+		"r":     uint32(8),
+		"alpha": uint32(160),
+	}
+	return kv
+}
+
+func (p *adapter) Tensors(ts []Tensor) []*llm.Tensor {
+	var out []*llm.Tensor
+	for _, t := range ts {
+		name := p.tensorName(t.Name())
+
+		out = append(out, &llm.Tensor{
+			Name:     name,
+			Kind:     t.Kind(),
+			Shape:    t.Shape(),
+			WriterTo: t,
+		})
+	}
+
+	return out
+}
+
+func (p *adapter) tensorName(n string) string {
+	return strings.NewReplacer(
+		"model.layers", "blk",
+		"self_attn.q_proj", "attn_q.weight",
+		"self_attn.k_proj", "attn_k.weight",
+		"self_attn.v_proj", "attn_v.weight",
+		"self_attn.o_proj", "attn_output.weight",
+		"lora_a", "loraA",
+		"lora_b", "loraB",
+		".npy", "",
+	).Replace(n)
+}

convert/convert_bert.go

@@ -1,174 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"encoding/json"
-	"io/fs"
-	"path/filepath"
-	"slices"
-	"strings"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type bertModel struct {
-	ModelParameters
-	NLayers               uint32  `json:"n_layers"`
-	NumHiddenLayers       uint32  `json:"num_hidden_layers"`
-	NLayer                uint32  `json:"n_layer"`
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	NCtx                  uint32  `json:"n_ctx"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	NEmbd                 uint32  `json:"n_embd"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
-	NInner                uint32  `json:"n_inner"`
-	NumAttentionHeads     uint32  `json:"num_attention_heads"`
-	NHead                 uint32  `json:"n_head"`
-	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-	LayerNormEPS          float32 `json:"layer_norm_eps"`
-	LayerNormEpsilon      float32 `json:"layer_norm_epsilon"`
-	NormEpsilon           float32 `json:"norm_epsilon"`
-
-	PoolingType uint32
-}
-
-var (
-	_ ModelConverter = (*bertModel)(nil)
-	_ moreParser     = (*bertModel)(nil)
-)
-
-func (p *bertModel) parseMore(fsys fs.FS) error {
-	bts, err := fs.ReadFile(fsys, "modules.json")
-	if err != nil {
-		return err
-	}
-
-	var modules []struct {
-		Type string `json:"type"`
-		Path string `json:"path"`
-	}
-
-	if err := json.Unmarshal(bts, &modules); err != nil {
-		return err
-	}
-
-	var pooling string
-	for _, m := range modules {
-		if m.Type == "sentence_transformers.models.Pooling" {
-			pooling = m.Path
-			break
-		}
-	}
-
-	if pooling != "" {
-		bts, err := fs.ReadFile(fsys, filepath.Join(pooling, "config.json"))
-		if err != nil {
-			return err
-		}
-
-		var pc struct {
-			PoolingModeCLSToken   bool `json:"pooling_mode_cls_token"`
-			PoolingModeMeanTokens bool `json:"pooling_mode_mean_tokens"`
-		}
-
-		if err := json.Unmarshal(bts, &pc); err != nil {
-			return err
-		}
-
-		if pc.PoolingModeMeanTokens {
-			p.PoolingType = 1
-		} else if pc.PoolingModeCLSToken {
-			p.PoolingType = 2
-		}
-	}
-
-	return nil
-}
-
-func (p *bertModel) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "bert"
-	kv["bert.attention.causal"] = false
-	kv["bert.pooling_type"] = p.PoolingType
-
-	kv["bert.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer)
-
-	if contextLength := cmp.Or(p.MaxPositionEmbeddings, p.NCtx); contextLength > 0 {
-		kv["bert.context_length"] = contextLength
-	}
-
-	if embeddingLength := cmp.Or(p.HiddenSize, p.NEmbd); embeddingLength > 0 {
-		kv["bert.embedding_length"] = cmp.Or(p.HiddenSize, p.NEmbd)
-	}
-
-	if feedForwardLength := cmp.Or(p.IntermediateSize, p.NInner); feedForwardLength > 0 {
-		kv["bert.feed_forward_length"] = cmp.Or(p.IntermediateSize, p.NInner)
-	}
-
-	if headCount := cmp.Or(p.NumAttentionHeads, p.NHead); headCount > 0 {
-		kv["bert.attention.head_count"] = cmp.Or(p.NumAttentionHeads, p.NHead)
-	}
-
-	if layerNormEpsilon := cmp.Or(p.LayerNormEPS, p.LayerNormEpsilon, p.NormEpsilon); layerNormEpsilon > 0 {
-		kv["bert.attention.layer_norm_epsilon"] = layerNormEpsilon
-	}
-
-	kv["tokenizer.ggml.model"] = "bert"
-	kv["tokenizer.ggml.token_type_count"] = uint32(2)
-
-	// convert to phantom space tokens
-	for i, e := range t.Tokens {
-		if strings.HasPrefix(e, "[") && strings.HasSuffix(e, "]") {
-			// noop
-		} else if strings.HasPrefix(e, "##") {
-			t.Tokens[i] = e[2:]
-		} else {
-			t.Tokens[i] = "\u2581" + e
-		}
-	}
-
-	kv["tokenizer.ggml.tokens"] = t.Tokens
-
-	return kv
-}
-
-func (p *bertModel) Tensors(ts []Tensor) []ggml.Tensor {
-	var out []ggml.Tensor
-	for _, t := range ts {
-		if slices.Contains([]string{
-			"embeddings.position_ids",
-			"pooler.dense.weight",
-			"pooler.dense.bias",
-		}, t.Name()) {
-			continue
-		}
-
-		out = append(out, ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (bertModel) Replacements() []string {
-	return []string{
-		"encoder.layer", "blk",
-		"encoder.layers", "blk",
-		"embeddings.word_embeddings", "token_embd",
-		"embeddings.token_type_embeddings", "token_types",
-		"embeddings.LayerNorm", "token_embd_norm",
-		"embeddings.position_embeddings", "position_embd",
-		"attention.self.query", "attn_q",
-		"attention.self.key", "attn_k",
-		"attention.self.value", "attn_v",
-		"attention.output.dense", "attn_output",
-		"attention.output.LayerNorm", "attn_output_norm",
-		"intermediate.dense", "ffn_up",
-		"output.dense", "ffn_down",
-		"output.LayerNorm", "layer_output_norm",
-	}
-}

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

@@ -6,11 +6,11 @@ import (
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/llm"
 )
 
-type gemmaModel struct {
-	ModelParameters
+type gemma struct {
+	Parameters
 	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
 	HiddenSize            uint32  `json:"hidden_size"`
 	HiddenLayers          uint32  `json:"num_hidden_layers"`
@@ -21,11 +21,12 @@ type gemmaModel struct {
 	HeadDim               uint32  `json:"head_dim"`
 }
 
-var _ ModelConverter = (*gemmaModel)(nil)
+var _ Converter = (*gemma)(nil)
 
-func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
+func (p *gemma) KV(t *Tokenizer) llm.KV {
+	kv := p.Parameters.KV(t)
 	kv["general.architecture"] = "gemma"
+	kv["general.name"] = "gemma"
 	kv["gemma.context_length"] = p.MaxPositionEmbeddings
 	kv["gemma.embedding_length"] = p.HiddenSize
 	kv["gemma.block_count"] = p.HiddenLayers
@@ -42,15 +43,16 @@ func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p *gemmaModel) Tensors(ts []Tensor) []ggml.Tensor {
-	var out []ggml.Tensor
+func (p *gemma) Tensors(ts []Tensor) []*llm.Tensor {
+	var out []*llm.Tensor
 	for _, t := range ts {
-		if !strings.HasPrefix(t.Name(), "v.") && strings.HasSuffix(t.Name(), "_norm.weight") {
+		name := p.tensorName(t.Name())
+		if strings.HasSuffix(name, "_norm.weight") {
 			t.SetRepacker(p.addOne)
 		}
 
-		out = append(out, ggml.Tensor{
-			Name:     t.Name(),
+		out = append(out, &llm.Tensor{
+			Name:     name,
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
 			WriterTo: t,
@@ -60,8 +62,8 @@ func (p *gemmaModel) Tensors(ts []Tensor) []ggml.Tensor {
 	return out
 }
 
-func (p *gemmaModel) Replacements() []string {
-	return []string{
+func (p *gemma) tensorName(n string) string {
+	return strings.NewReplacer(
 		"model.embed_tokens", "token_embd",
 		"model.norm", "output_norm",
 		"model.layers", "blk",
@@ -74,10 +76,11 @@ func (p *gemmaModel) Replacements() []string {
 		"mlp.down_proj", "ffn_down",
 		"mlp.up_proj", "ffn_up",
 		"post_attention_layernorm", "ffn_norm",
-	}
+		"block_sparse_moe.gate", "ffn_inp",
+	).Replace(n)
 }
 
-func (*gemmaModel) addOne(_ string, data []float32, shape []uint64) ([]float32, error) {
+func (*gemma) addOne(_ string, data []float32, shape []uint64) ([]float32, error) {
 	n := tensor.New(tensor.WithShape(int(shape[0])), tensor.WithBacking(data))
 	ones := tensor.Ones(tensor.Float32, int(shape[0]))
 

convert/convert_gemma2.go

@@ -1,51 +0,0 @@
-package convert
-
-import "github.com/ollama/ollama/fs/ggml"
-
-type gemma2Model struct {
-	gemmaModel
-	SlidingWindow         uint32  `json:"sliding_window"`
-	AttentionLogitSoftcap float32 `json:"attn_logit_softcapping"`
-	FinalLogitSoftcap     float32 `json:"final_logit_softcapping"`
-}
-
-func (p *gemma2Model) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "gemma2"
-	kv["gemma2.context_length"] = p.MaxPositionEmbeddings
-	kv["gemma2.embedding_length"] = p.HiddenSize
-	kv["gemma2.block_count"] = p.HiddenLayers
-	kv["gemma2.feed_forward_length"] = p.IntermediateSize
-	kv["gemma2.attention.head_count"] = p.NumAttentionHeads
-	kv["gemma2.attention.head_count_kv"] = p.NumKeyValueHeads
-	kv["gemma2.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
-	kv["gemma2.attention.key_length"] = p.HeadDim
-	kv["gemma2.attention.value_length"] = p.HeadDim
-	kv["gemma2.attention.sliding_window"] = p.SlidingWindow
-	kv["gemma2.attn_logit_softcapping"] = p.AttentionLogitSoftcap
-	kv["gemma2.final_logit_softcapping"] = p.FinalLogitSoftcap
-	kv["tokenizer.ggml.eot_token_id"] = uint32(107)
-	kv["tokenizer.ggml.middle_token_id"] = uint32(68)
-	kv["tokenizer.ggml.prefix_token_id"] = uint32(67)
-	kv["tokenizer.ggml.suffix_token_id"] = uint32(69)
-	return kv
-}
-
-func (p *gemma2Model) Replacements() []string {
-	return []string{
-		"model.embed_tokens", "token_embd",
-		"model.norm", "output_norm",
-		"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_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",
-	}
-}

convert/convert_gemma2_adapter.go

@@ -1,91 +0,0 @@
-package convert
-
-import (
-	"strings"
-
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type gemma2Adapter struct {
-	AdapterParameters
-}
-
-var _ AdapterConverter = (*gemma2Adapter)(nil)
-
-func (p *gemma2Adapter) KV(baseKV ggml.KV) ggml.KV {
-	kv := p.AdapterParameters.KV()
-	kv["general.architecture"] = "gemma2"
-	return kv
-}
-
-func (p *gemma2Adapter) Tensors(ts []Tensor) []ggml.Tensor {
-	var out []ggml.Tensor
-	for _, t := range ts {
-		shape := t.Shape()
-		if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
-			(strings.HasSuffix(t.Name(), "weight.lora_b") && shape[0] < shape[1]) {
-			shape[0], shape[1] = shape[1], shape[0]
-			t.SetRepacker(p.repack)
-		}
-
-		out = append(out, ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *gemma2Adapter) Replacements() []string {
-	return []string{
-		"base_model.model.", "",
-		"model.layers", "blk",
-		"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.gate_proj", "ffn_gate",
-		"mlp.down_proj", "ffn_down",
-		"mlp.up_proj", "ffn_up",
-		"lora_A.weight", "weight.lora_a",
-		"lora_B.weight", "weight.lora_b",
-		"lora_a", "weight.lora_a",
-		"lora_b", "weight.lora_b",
-	}
-}
-
-func (p *gemma2Adapter) repack(name string, data []float32, shape []uint64) ([]float32, error) {
-	dims := []int{int(shape[1]), int(shape[0])}
-
-	n := tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-
-	if err := n.T(1, 0); 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_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_llama.go

@@ -3,17 +3,15 @@ package convert
 import (
 	"cmp"
 	"fmt"
-	"math"
 	"strings"
 
+	"github.com/ollama/ollama/llm"
 	"github.com/pdevine/tensor"
 	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
 )
 
-type llamaModel struct {
-	ModelParameters
+type llama struct {
+	Parameters
 	NLayers               uint32  `json:"n_layers"`
 	NumHiddenLayers       uint32  `json:"num_hidden_layers"`
 	NLayer                uint32  `json:"n_layer"`
@@ -28,27 +26,21 @@ 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"`
-		OriginalMaxPositionalEmbeddings uint32  `json:"original_max_positional_embeddings"`
-
-		factors ropeFactor
+		Type   string  `json:"type"`
+		Factor float32 `json:"factor"`
 	} `json:"rope_scaling"`
 	RMSNormEPS       float32 `json:"rms_norm_eps"`
 	LayerNormEPS     float32 `json:"layer_norm_eps"`
 	LayerNormEpsilon float32 `json:"layer_norm_epsilon"`
 	NormEpsilon      float32 `json:"norm_epsilon"`
-	HeadDim          uint32  `json:"head_dim"`
 }
 
-var _ ModelConverter = (*llamaModel)(nil)
+var _ Converter = (*llama)(nil)
 
-func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
+func (p *llama) KV(t *Tokenizer) llm.KV {
+	kv := p.Parameters.KV(t)
 	kv["general.architecture"] = "llama"
+	kv["general.name"] = "llama"
 	kv["llama.vocab_size"] = p.VocabSize
 
 	kv["llama.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer)
@@ -77,27 +69,6 @@ func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
 	if p.RopeScaling.Type == "linear" {
 		kv["llama.rope.scaling.type"] = p.RopeScaling.Type
 		kv["llama.rope.scaling.factor"] = p.RopeScaling.Factor
-	} else if p.RopeScaling.RopeType == "llama3" {
-		dim := p.HiddenSize / p.NumAttentionHeads
-		for i := uint32(0); i < dim; i += 2 {
-			factor := cmp.Or(p.RopeScaling.Factor, 8.0)
-			factorLow := cmp.Or(p.RopeScaling.LowFrequencyFactor, 1.0)
-			factorHigh := cmp.Or(p.RopeScaling.HighFrequencyFactor, 4.0)
-
-			original := cmp.Or(p.RopeScaling.OriginalMaxPositionalEmbeddings, 8192)
-			lambdaLow := float32(original) / factorLow
-			lambdaHigh := float32(original) / factorHigh
-
-			lambda := 2 * math.Pi * math.Pow(float64(p.RopeTheta), float64(i)/float64(dim))
-			if lambda < float64(lambdaHigh) {
-				p.RopeScaling.factors = append(p.RopeScaling.factors, 1.0)
-			} else if lambda > float64(lambdaLow) {
-				p.RopeScaling.factors = append(p.RopeScaling.factors, factor)
-			} else {
-				smooth := (float32(original)/float32(lambda) - factorLow) / (factorHigh - factorLow)
-				p.RopeScaling.factors = append(p.RopeScaling.factors, 1.0/((1-smooth)/factor+smooth))
-			}
-		}
 	}
 
 	if p.NumKeyValueHeads > 0 {
@@ -112,34 +83,24 @@ func (p *llamaModel) KV(t *Tokenizer) ggml.KV {
 		kv["llama.attention.layer_norm_epsilon"] = layerNormEpsilon
 	}
 
-	if p.HeadDim > 0 {
-		kv["llama.attention.key_length"] = p.HeadDim
-		kv["llama.attention.value_length"] = p.HeadDim
+	if len(t.Merges) > 0 {
+		kv["tokenizer.ggml.merges"] = t.Merges
 	}
 
 	return kv
 }
 
-func (p *llamaModel) Tensors(ts []Tensor) []ggml.Tensor {
-	var out []ggml.Tensor
-
-	if p.RopeScaling.factors != nil {
-		out = append(out, ggml.Tensor{
-			Name:     "rope_freqs.weight",
-			Kind:     0,
-			Shape:    []uint64{uint64(len(p.RopeScaling.factors))},
-			WriterTo: p.RopeScaling.factors,
-		})
-	}
-
+func (p *llama) Tensors(ts []Tensor) []*llm.Tensor {
+	var out []*llm.Tensor
 	for _, t := range ts {
-		if strings.HasSuffix(t.Name(), "attn_q.weight") ||
-			strings.HasSuffix(t.Name(), "attn_k.weight") {
+		name := p.tensorName(t.Name())
+		if strings.HasSuffix(name, "attn_q.weight") ||
+			strings.HasSuffix(name, "attn_k.weight") {
 			t.SetRepacker(p.repack)
 		}
 
-		out = append(out, ggml.Tensor{
-			Name:     t.Name(),
+		out = append(out, &llm.Tensor{
+			Name:     name,
 			Kind:     t.Kind(),
 			Shape:    t.Shape(),
 			WriterTo: t,
@@ -149,8 +110,8 @@ func (p *llamaModel) Tensors(ts []Tensor) []ggml.Tensor {
 	return out
 }
 
-func (p *llamaModel) Replacements() []string {
-	return []string{
+func (p *llama) tensorName(n string) string {
+	return strings.NewReplacer(
 		"lm_head", "output",
 		"model.embed_tokens", "token_embd",
 		"model.norm", "output_norm",
@@ -164,19 +125,21 @@ func (p *llamaModel) Replacements() []string {
 		"mlp.down_proj", "ffn_down",
 		"mlp.up_proj", "ffn_up",
 		"post_attention_layernorm", "ffn_norm",
-	}
+		// mixtral
+		"block_sparse_moe.gate", "ffn_gate_inp",
+	).Replace(n)
 }
 
-func (p *llamaModel) repack(name string, data []float32, shape []uint64) ([]float32, error) {
+func (p *llama) 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") {
+	if strings.HasSuffix(name, "q_proj.weight") {
 		heads = p.NumAttentionHeads
-	} else if strings.HasSuffix(name, "attn_k.weight") {
+	} else if strings.HasSuffix(name, "k_proj.weight") {
 		heads = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
 	} else {
 		return nil, fmt.Errorf("unknown tensor for repack: %s", name)

convert/convert_llama_adapter.go

@@ -1,169 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"strings"
-
-	"github.com/pdevine/tensor"
-	"github.com/pdevine/tensor/native"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type llamaAdapter struct {
-	AdapterParameters
-	NumAttentionHeads uint32 `json:"num_attention_heads"`
-	NumKeyValueHeads  uint32 `json:"num_key_value_heads"`
-}
-
-var _ AdapterConverter = (*llamaAdapter)(nil)
-
-func (p *llamaAdapter) KV(baseKV ggml.KV) ggml.KV {
-	kv := p.AdapterParameters.KV()
-	kv["general.architecture"] = "llama"
-	kv["llama.attention.head_count"] = baseKV["llama.attention.head_count"]
-	kv["llama.attention.head_count_kv"] = baseKV["llama.attention.head_count_kv"]
-
-	p.NumAttentionHeads = baseKV["llama.attention.head_count"].(uint32)
-
-	return kv
-}
-
-func (p *llamaAdapter) Tensors(ts []Tensor) []ggml.Tensor {
-	var out []ggml.Tensor
-	for _, t := range ts {
-		shape := t.Shape()
-		if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
-			(strings.HasSuffix(t.Name(), "weight.lora_b") && shape[0] < shape[1]) {
-			shape[0], shape[1] = shape[1], shape[0]
-			t.SetRepacker(p.repackAndTranspose)
-		} else {
-			t.SetRepacker(p.repack)
-		}
-
-		out = append(out, ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    shape,
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *llamaAdapter) Replacements() []string {
-	return []string{
-		"base_model.model.", "",
-		"model.layers", "blk",
-		"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.gate_proj", "ffn_gate",
-		"mlp.down_proj", "ffn_down",
-		"mlp.up_proj", "ffn_up",
-		"lora_A.weight", "weight.lora_a",
-		"lora_B.weight", "weight.lora_b",
-		"lora_a", "weight.lora_a",
-		"lora_b", "weight.lora_b",
-	}
-}
-
-func (p *llamaAdapter) repack(name string, data []float32, shape []uint64) ([]float32, error) {
-	dims := []int{int(shape[1]), int(shape[0])}
-
-	var heads uint32
-	if strings.HasSuffix(name, "attn_q.weight.lora_a") {
-		heads = p.NumAttentionHeads
-	} else if strings.HasSuffix(name, "attn_k.weight.lora_a") {
-		heads = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
-	} else {
-		return data, nil
-	}
-
-	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
-}
-
-func (p *llamaAdapter) repackAndTranspose(name string, data []float32, shape []uint64) ([]float32, error) {
-	dims := []int{int(shape[1]), int(shape[0])}
-
-	n := tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
-
-	var heads uint32
-	if strings.HasSuffix(name, "attn_q.weight.lora_a") {
-		heads = p.NumAttentionHeads
-	} else if strings.HasSuffix(name, "attn_k.weight.lora_a") {
-		heads = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
-	}
-
-	if heads > 0 {
-		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
-		}
-	}
-
-	if err := n.T(1, 0); 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_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

@@ -6,17 +6,19 @@ import (
 	"slices"
 	"strings"
 
-	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/llm"
 )
 
-type mixtralModel struct {
-	llamaModel
+type mixtral struct {
+	llama
 	NumLocalExperts    uint32 `json:"num_local_experts"`
 	NumExpertsPerToken uint32 `json:"num_experts_per_tok"`
 }
 
-func (p *mixtralModel) KV(t *Tokenizer) ggml.KV {
-	kv := p.llamaModel.KV(t)
+var _ Converter = (*mixtral)(nil)
+
+func (p *mixtral) KV(t *Tokenizer) llm.KV {
+	kv := p.llama.KV(t)
 
 	if p.NumLocalExperts > 0 {
 		kv["llama.expert_count"] = p.NumLocalExperts
@@ -29,7 +31,7 @@ func (p *mixtralModel) KV(t *Tokenizer) ggml.KV {
 	return kv
 }
 
-func (p *mixtralModel) Tensors(ts []Tensor) []ggml.Tensor {
+func (p *mixtral) Tensors(ts []Tensor) []*llm.Tensor {
 	oldnew := []string{
 		"model.layers", "blk",
 		"w1", "ffn_gate_exps",
@@ -56,10 +58,10 @@ func (p *mixtralModel) Tensors(ts []Tensor) []ggml.Tensor {
 		return true
 	})
 
-	var out []ggml.Tensor
+	var out []*llm.Tensor
 	for n, e := range experts {
 		// TODO(mxyng): sanity check experts
-		out = append(out, ggml.Tensor{
+		out = append(out, &llm.Tensor{
 			Name:     n,
 			Kind:     e[0].Kind(),
 			Shape:    append([]uint64{uint64(len(e))}, e[0].Shape()...),
@@ -67,14 +69,7 @@ func (p *mixtralModel) Tensors(ts []Tensor) []ggml.Tensor {
 		})
 	}
 
-	return append(out, p.llamaModel.Tensors(ts)...)
-}
-
-func (p *mixtralModel) Replacements() []string {
-	return append(
-		p.llamaModel.Replacements(),
-		"block_sparse_moe.gate", "ffn_gate_inp",
-	)
+	return append(out, p.llama.Tensors(ts)...)
 }
 
 type experts []Tensor

convert/convert_phi3.go

@@ -1,123 +0,0 @@
-package convert
-
-import (
-	"cmp"
-	"encoding/binary"
-	"io"
-	"math"
-	"strings"
-	"sync"
-
-	"github.com/ollama/ollama/fs/ggml"
-)
-
-type phi3Model struct {
-	ModelParameters
-	NumHiddenLayers   uint32  `json:"num_hidden_layers"`
-	NLayers           uint32  `json:"n_layers"`
-	HiddenSize        uint32  `json:"hidden_size"`
-	NEmbd             uint32  `json:"n_embd"`
-	IntermediateSize  uint32  `json:"intermediate_size"`
-	NumAttentionHeads uint32  `json:"num_attention_heads"`
-	NHead             uint32  `json:"n_head"`
-	NumKeyValueHeads  uint32  `json:"num_key_value_heads"`
-	NHeadKV           uint32  `json:"n_head_kv"`
-	RopeTheta         float32 `json:"rope_theta"`
-	RopeScaling       struct {
-		Type        string     `json:"type"`
-		LongFactor  ropeFactor `json:"long_factor"`
-		ShortFactor ropeFactor `json:"short_factor"`
-	} `json:"rope_scaling"`
-	RMSNormEPS                    float32 `json:"rms_norm_eps"`
-	NPositions                    uint32  `json:"n_positions"`
-	MaxPositionEmbeddings         uint32  `json:"max_position_embeddings"`
-	OriginalMaxPositionEmbeddings uint32  `json:"original_max_position_embeddings"`
-	SlidingWindow                 uint32  `json:"sliding_window"`
-}
-
-var _ ModelConverter = (*phi3Model)(nil)
-
-func (p *phi3Model) KV(t *Tokenizer) ggml.KV {
-	kv := p.ModelParameters.KV(t)
-	kv["general.architecture"] = "phi3"
-	kv["phi3.context_length"] = p.MaxPositionEmbeddings
-	kv["phi3.embedding_length"] = cmp.Or(p.HiddenSize, p.NEmbd)
-	kv["phi3.feed_forward_length"] = p.IntermediateSize
-	kv["phi3.block_count"] = cmp.Or(p.NumHiddenLayers, p.NLayers)
-	kv["phi3.attention.head_count"] = cmp.Or(p.NumAttentionHeads, p.NHead)
-	kv["phi3.attention.head_count_kv"] = cmp.Or(p.NumKeyValueHeads, p.NHeadKV)
-	kv["phi3.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
-	kv["phi3.rope.dimension_count"] = p.HiddenSize / cmp.Or(p.NumAttentionHeads, p.NHead)
-	kv["phi3.rope.freq_base"] = p.RopeTheta
-	kv["phi3.rope.scaling.original_context_length"] = p.OriginalMaxPositionEmbeddings
-	kv["phi3.attention.sliding_window"] = p.SlidingWindow
-
-	scale := float64(p.MaxPositionEmbeddings) / float64(p.OriginalMaxPositionEmbeddings)
-
-	switch p.RopeScaling.Type {
-	case "":
-		// no scaling
-	case "su", "longrope":
-		kv["phi3.rope.scaling.attn_factor"] = float32(max(math.Sqrt(1+math.Log(scale)/math.Log(float64(p.OriginalMaxPositionEmbeddings))), 1.0))
-	case "yarn":
-		kv["phi3.rope.scaling.attn_factor"] = float32(max(0.1*math.Log(scale)+1.0, 1.0))
-	default:
-		panic("unknown rope scaling type")
-	}
-
-	return kv
-}
-
-func (p *phi3Model) Tensors(ts []Tensor) []ggml.Tensor {
-	var addRopeFactors sync.Once
-
-	out := make([]ggml.Tensor, 0, len(ts)+2)
-	for _, t := range ts {
-		if strings.HasPrefix(t.Name(), "blk.0.") {
-			addRopeFactors.Do(func() {
-				out = append(out, ggml.Tensor{
-					Name:     "rope_factors_long.weight",
-					Kind:     0,
-					Shape:    []uint64{uint64(len(p.RopeScaling.LongFactor))},
-					WriterTo: p.RopeScaling.LongFactor,
-				}, ggml.Tensor{
-					Name:     "rope_factors_short.weight",
-					Kind:     0,
-					Shape:    []uint64{uint64(len(p.RopeScaling.ShortFactor))},
-					WriterTo: p.RopeScaling.ShortFactor,
-				})
-			})
-		}
-
-		out = append(out, ggml.Tensor{
-			Name:     t.Name(),
-			Kind:     t.Kind(),
-			Shape:    t.Shape(),
-			WriterTo: t,
-		})
-	}
-
-	return out
-}
-
-func (p *phi3Model) Replacements() []string {
-	return []string{
-		"lm_head", "output",
-		"model.embed_tokens", "token_embd",
-		"model.norm", "output_norm",
-		"model.layers", "blk",
-		"input_layernorm", "attn_norm",
-		"self_attn.qkv_proj", "attn_qkv",
-		"self_attn.o_proj", "attn_output",
-		"mlp.down_proj", "ffn_down",
-		"mlp.gate_up_proj", "ffn_up",
-		"post_attention_layernorm", "ffn_norm",
-	}
-}
-
-type ropeFactor []float32
-
-func (r ropeFactor) WriteTo(w io.Writer) (int64, error) {
-	err := binary.Write(w, binary.LittleEndian, r)
-	return 0, err
-}

convert/convert_qwen2.go

@@ -1,78 +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"`
-	} `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
-	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_test.go

@@ -3,33 +3,23 @@ package convert
 import (
 	"bytes"
 	"crypto/sha256"
-	"encoding/binary"
-	"encoding/hex"
 	"encoding/json"
+	"errors"
 	"flag"
 	"fmt"
 	"io"
-	"io/fs"
 	"log/slog"
 	"math"
 	"os"
 	"path/filepath"
 	"slices"
-	"strings"
 	"testing"
 
+	"github.com/ollama/ollama/llm"
 	"golang.org/x/exp/maps"
-
-	"github.com/ollama/ollama/fs/ggml"
 )
 
-type tensorData struct {
-	Offsets []int  `json:"data_offsets"`
-	Type    string `json:"dtype"`
-	Shape   []int  `json:"shape"`
-}
-
-func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
+func convertFull(t *testing.T, d string) (*os.File, llm.KV, llm.Tensors) {
 	t.Helper()
 
 	f, err := os.CreateTemp(t.TempDir(), "f16")
@@ -38,7 +28,7 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
 	}
 	defer f.Close()
 
-	if err := ConvertModel(fsys, f); err != nil {
+	if err := Convert(d, f); err != nil {
 		t.Fatal(err)
 	}
 
@@ -48,7 +38,7 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, ggml.KV, ggml.Tensors) {
 	}
 	t.Cleanup(func() { r.Close() })
 
-	m, _, err := ggml.Decode(r, math.MaxInt)
+	m, _, err := llm.DecodeGGML(r, math.MaxInt)
 	if err != nil {
 		t.Fatal(err)
 	}
@@ -60,34 +50,6 @@ 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 {
-	actual := make(map[string]string)
-	for k, v := range kv {
-		if s, ok := v.(json.Marshaler); !ok {
-			actual[k] = fmt.Sprintf("%v", v)
-		} else {
-			bts, err := json.Marshal(s)
-			if err != nil {
-				t.Fatal(err)
-			}
-
-			actual[k] = fmt.Sprintf("%x", sha256.Sum256(bts))
-		}
-	}
-
-	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 {
-			t.Fatal(err)
-		}
-
-		actual[tensor.Name] = hex.EncodeToString(sha256sum.Sum(nil))
-	}
-
-	return actual
-}
-
 func TestMain(m *testing.M) {
 	var level slog.Level
 	flag.TextVar(&level, "level", slog.LevelInfo, "log level")
@@ -96,20 +58,12 @@ func TestMain(m *testing.M) {
 	os.Exit(m.Run())
 }
 
-func TestConvertModel(t *testing.T) {
+func TestConvertFull(t *testing.T) {
 	cases := []string{
 		"Meta-Llama-3-8B-Instruct",
-		"Meta-Llama-3.1-8B-Instruct",
 		"Mistral-7B-Instruct-v0.2",
 		"Mixtral-8x7B-Instruct-v0.1",
 		"gemma-2b-it",
-		"gemma-2-2b-it",
-		// microsoft/Phi-3-mini-128-instruct@d548c233192db00165d842bf8edff054bb3212f8
-		"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 {
@@ -124,8 +78,30 @@ func TestConvertModel(t *testing.T) {
 				t.Skipf("%s not found", p)
 			}
 
-			f, kv, tensors := convertFull(t, os.DirFS(p))
-			actual := generateResultsJSON(t, f, kv, tensors)
+			f, kv, tensors := convertFull(t, p)
+			actual := make(map[string]string)
+			for k, v := range kv {
+				if s, ok := v.(json.Marshaler); !ok {
+					actual[k] = fmt.Sprintf("%v", v)
+				} else {
+					bts, err := json.Marshal(s)
+					if err != nil {
+						t.Fatal(err)
+					}
+
+					actual[k] = fmt.Sprintf("%x", sha256.Sum256(bts))
+				}
+			}
+
+			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 {
+					t.Fatal(err)
+				}
+
+				actual[tensor.Name] = fmt.Sprintf("%x", sha256sum.Sum(nil))
+			}
 
 			expectFile, err := os.Open(filepath.Join("testdata", fmt.Sprintf("%s.json", tt)))
 			if err != nil {
@@ -150,329 +126,110 @@ func TestConvertModel(t *testing.T) {
 	}
 }
 
-func TestConvertInvalidTensorNames(t *testing.T) {
-	f, err := os.CreateTemp(t.TempDir(), "testmodel")
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer f.Close()
-
-	tempDir := t.TempDir()
-
-	td := map[string]*tensorData{}
-	offset := 4096
-
-	td["model.layers.0.self_attn.q_proj.weight"] = &tensorData{
-		Offsets: []int{0, offset},
-		Type:    "F32",
-		Shape:   []int{4096, 4096},
-	}
-	td["blk.0.attn_q.weight"] = &tensorData{
-		Offsets: []int{offset, offset * 2},
-		Type:    "F32",
-		Shape:   []int{4096, 4096},
-	}
-	generateSafetensorTestData(t, tempDir, td)
-
-	err = ConvertModel(os.DirFS(tempDir), f)
-	if err == nil || !strings.HasPrefix(err.Error(), "duplicate tensor name") {
-		t.Errorf("expected error but didn't get one")
-	}
-}
-
-func TestConvertInvalidDatatype(t *testing.T) {
-	f, err := os.CreateTemp(t.TempDir(), "testmodel")
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer f.Close()
-
-	tempDir := t.TempDir()
-
-	td := map[string]*tensorData{}
-	offset := 4096 * 14336
-
-	td["model.layers.0.mlp.down_proj.weight"] = &tensorData{
-		Offsets: []int{0, offset},
-		Type:    "I8",
-		Shape:   []int{4096, 14336},
-	}
-	td["model.layers.0.mlp.down_proj.weight_format"] = &tensorData{
-		Offsets: []int{offset, offset},
-		Type:    "U8",
-		Shape:   []int{},
-	}
-	generateSafetensorTestData(t, tempDir, td)
-
-	err = ConvertModel(os.DirFS(tempDir), f)
-	if err == nil || err.Error() != "unsupported safetensors model" {
-		t.Errorf("expected error but didn't get one")
-	}
-}
-
-func generateSafetensorTestData(t *testing.T, tempDir string, tensorData map[string]*tensorData) {
-	data, err := json.Marshal(tensorData)
-	if err != nil {
-		t.Fatal(err)
+func TestConvertNPZ(t *testing.T) {
+	cases := []string{
+		"adapters.npz",
 	}
 
-	var buf bytes.Buffer
-
-	l := int64(len(data))
-	err = binary.Write(&buf, binary.LittleEndian, l)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	_, err = buf.Write(data)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	fdata, err := os.Create(filepath.Join(tempDir, "model-00001-of-00001.safetensors"))
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer fdata.Close()
-
-	_, err = fdata.Write(buf.Bytes())
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	configData := `
-{
-  "architectures": [
-    "LlamaForCausalLM"
-  ]
-}
-`
-
-	f, err := os.Create(filepath.Join(tempDir, "config.json"))
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer f.Close()
-
-	_, err = f.WriteString(configData)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	tokenizerData := `
-{
-}
-`
-
-	f, err = os.Create(filepath.Join(tempDir, "tokenizer.json"))
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer f.Close()
-
-	_, err = f.WriteString(tokenizerData)
-	if err != nil {
-		t.Fatal(err)
-	}
-}
-
-func TestConvertAdapter(t *testing.T) {
-	type AdapterCase struct {
-		Name     string
-		BaseKV   map[string]any
-		Expected map[string]string
-	}
-
-	cases := []AdapterCase{
-		{
-			Name: "discollama",
-			BaseKV: map[string]any{
-				"general.architecture":          "llama",
-				"llama.attention.head_count":    uint32(32),
-				"llama.attention.head_count_kv": uint32(8),
-			},
-			Expected: map[string]string{
-				"general.architecture":          "llama",
-				"general.file_type":             "1",
-				"general.parameter_count":       "106496",
-				"general.type":                  "adapter",
-				"general.version":               "v0.2",
-				"adapter.lora.alpha":            "16",
-				"adapter.type":                  "lora",
-				"llama.attention.head_count":    "32",
-				"llama.attention.head_count_kv": "8",
-				"blk.31.attn_q.weight.lora_a":   "0eb3318b02cd313429bcc7621b539fdbb10240fea190c56c9e5f93fcd37a4e50",
-				"blk.31.attn_q.weight.lora_b":   "0eb3318b02cd313429bcc7621b539fdbb10240fea190c56c9e5f93fcd37a4e50",
-				"blk.31.attn_v.weight.lora_a":   "0eb3318b02cd313429bcc7621b539fdbb10240fea190c56c9e5f93fcd37a4e50",
-				"blk.31.attn_v.weight.lora_b":   "071dcafe89df065d6e1c935ecb8fdf6479b3c202eb912e7da938597673ff5857",
-			},
-		},
-	}
-
-	for _, c := range cases {
-		t.Run(c.Name, func(t *testing.T) {
-			t.Parallel()
-
-			f, err := os.CreateTemp(t.TempDir(), "f16")
-			if err != nil {
-				t.Fatal(err)
-			}
-			defer f.Close()
-
-			tempDir := t.TempDir()
-			generateLoraTestData(t, tempDir)
-
-			if err = ConvertAdapter(os.DirFS(tempDir), f, c.BaseKV); err != nil {
-				t.Fatal(err)
-			}
-
-			r, err := os.Open(f.Name())
-			if err != nil {
-				t.Fatal(err)
-			}
-			defer r.Close()
-
-			m, _, err := ggml.Decode(r, math.MaxInt)
-			if err != nil {
-				t.Fatal(err)
-			}
-
-			if _, err := r.Seek(0, io.SeekStart); err != nil {
-				t.Fatal(err)
-			}
-
-			actual := generateResultsJSON(t, r, m.KV(), m.Tensors())
-
-			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] {
-					t.Errorf("unexpected %s: want %s, got %s", k, c.Expected[k], v)
-				}
-			}
-		})
-	}
-}
-
-func generateLoraTestData(t *testing.T, tempDir string) {
-	offset := 4096 * 8 * 4
-
-	td := map[string]*tensorData{"__metadata__": nil}
-	td["model.layers.31.self_attn.q_proj.lora_a"] = &tensorData{
-		Offsets: []int{0, offset},
-		Type:    "F32",
-		Shape:   []int{4096, 8},
-	}
-	td["model.layers.31.self_attn.q_proj.lora_b"] = &tensorData{
-		Offsets: []int{offset, offset * 2},
-		Type:    "F32",
-		Shape:   []int{8, 4096},
-	}
-	td["model.layers.31.self_attn.v_proj.lora_a"] = &tensorData{
-		Offsets: []int{offset * 2, offset * 3},
-		Type:    "F32",
-		Shape:   []int{4096, 8},
-	}
-	td["model.layers.31.self_attn.v_proj.lora_b"] = &tensorData{
-		Offsets: []int{offset * 3, offset*3 + 8*1024*4},
-		Type:    "F32",
-		Shape:   []int{8, 1024},
-	}
-
-	data, err := json.Marshal(td)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	var buf bytes.Buffer
-
-	l := int64(len(data))
-	err = binary.Write(&buf, binary.LittleEndian, l)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	_, err = buf.Write(data)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	// write some data for the tensors
-
-	ones := make([]float32, 4096*8)
-	for i := range ones {
-		ones[i] = float32(1)
-	}
-
-	for range 3 {
-		err = binary.Write(&buf, binary.LittleEndian, ones)
+	for _, fn := range cases {
+		ts, err := parseNPZ(filepath.Join("testdata", fn))
 		if err != nil {
 			t.Fatal(err)
 		}
-	}
+		if len(ts) != 16*2*2 {
+			t.Errorf("got: %d want: %d total layers", len(ts), 16*2*2)
+		}
 
-	ones = make([]float32, 1024*8)
-	for i := range ones {
-		ones[i] = float32(1)
-	}
+		a := adapter{}
 
-	err = binary.Write(&buf, binary.LittleEndian, ones)
-	if err != nil {
-		t.Fatal(err)
-	}
+		for _, m := range ts {
+			at := m.(adapterTensor)
+			if at.path != filepath.Join("testdata", fn) {
+				t.Errorf("got: %s want: %s", at.path, filepath.Join("testdata", fn))
+			}
+			if at.dtype != "F32" {
+				t.Errorf("got: %s but only F32s are currently supported", at.dtype)
+			}
+			if len(at.tensorBase.shape) != 2 {
+				t.Errorf("got: %d want: %d tensor shape", at.tensorBase.shape, 2)
+			}
+		}
 
-	fdata, err := os.Create(filepath.Join(tempDir, "adapters.safetensors"))
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer fdata.Close()
+		var ws io.WriteSeeker = &memWriter{}
+		err = llm.WriteGGLA(ws, a.KV(nil), a.Tensors(ts))
+		if err != nil {
+			t.Fatal(err)
+		}
 
-	_, err = fdata.Write(buf.Bytes())
-	if err != nil {
-		t.Fatal(err)
-	}
+		mw := ws.(*memWriter)
+		slog.Info(fmt.Sprintf("buffer len = %d", len(mw.buf)))
+		if len(mw.buf) == 0 {
+			t.Errorf("ggla layer not written correctly")
+		}
+		rs := bytes.NewReader(mw.buf)
+		ggml, _, err := llm.DecodeGGML(rs, len(mw.buf))
+		if err != nil {
+			t.Fatal(err)
+		}
+		if ggml == nil {
+			t.Fatalf("ggla didn't convert to ggml correctly")
+		}
 
-	configData := `
-{
-    "adapter_path": "adapters-test",
-    "batch_size": 8,
-    "config": "config-tiny.json",
-    "data": "../discollama-completion",
-    "grad_checkpoint": null,
-    "iters": 1000,
-    "learning_rate": 1e-05,
-    "lora_layers": 1,
-    "lora_parameters": {
-        "rank": 8,
-        "alpha": 16,
-        "dropout": 0.0,
-        "scale": 2.0
-    },
-    "lr_schedule": null,
-    "max_seq_length": 2048,
-    "model": "/Users/pdevine/git/Meta-Llama-3-8B-Instruct",
-    "resume_adapter_file": null,
-    "save_every": 100,
-    "seed": 0,
-    "steps_per_eval": 200,
-    "steps_per_report": 10,
-    "test": false,
-    "test_batches": 500,
-    "train": true,
-    "use_dora": false,
-    "val_batches": 25
-}
-`
-	f, err := os.Create(filepath.Join(tempDir, "adapter_config.json"))
-	if err != nil {
-		t.Fatal(err)
-	}
-	defer f.Close()
+		kv := ggml.KV()
+		if kv == nil {
+			t.Fatalf("no lora KVs were set")
+		}
 
-	_, err = f.WriteString(configData)
-	if err != nil {
-		t.Fatal(err)
+		r, ok := kv["r"]
+		if !ok || r != uint32(8) {
+			t.Errorf("lora rank was not set correctly")
+		}
+
+		alpha, ok := kv["alpha"]
+		if !ok || alpha != uint32(160) {
+			t.Errorf("lora alpha was not set correctly")
+		}
+
+		gts := ggml.Tensors()
+		if len(ts) != len(gts.Items) {
+			t.Fatalf("got: %d want: %d tensors in ggla", len(gts.Items), len(ts))
+		}
 	}
 }
+
+type memWriter struct {
+	buf []byte
+	pos int
+}
+
+func (m *memWriter) Write(p []byte) (n int, err error) {
+	minCap := m.pos + len(p)
+	if minCap > cap(m.buf) {
+		buf2 := make([]byte, len(m.buf), minCap+len(p)) // add some extra
+		copy(buf2, m.buf)
+		m.buf = buf2
+	}
+	if minCap > len(m.buf) {
+		m.buf = m.buf[:minCap]
+	}
+	copy(m.buf[m.pos:], p)
+	m.pos += len(p)
+	return len(p), nil
+}
+
+func (m *memWriter) Seek(offset int64, whence int) (int64, error) {
+	newPos, offs := 0, int(offset)
+	switch whence {
+	case io.SeekStart:
+		newPos = offs
+	case io.SeekCurrent:
+		newPos = m.pos + offs
+	case io.SeekEnd:
+		newPos = len(m.buf) + offs
+	}
+	if newPos < 0 {
+		return 0, errors.New("negative result pos")
+	}
+	m.pos = newPos
+	return int64(newPos), nil
+}

convert/fs.go

@@ -1,58 +0,0 @@
-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

@@ -3,7 +3,7 @@ package convert
 import (
 	"errors"
 	"io"
-	"io/fs"
+	"path/filepath"
 	"strings"
 )
 
@@ -29,15 +29,8 @@ func (t tensorBase) Shape() []uint64 {
 	return t.shape
 }
 
-const (
-	tensorKindF32 uint32 = iota
-	tensorKindF16
-)
-
 func (t tensorBase) Kind() uint32 {
-	if strings.HasSuffix(t.name, ".ffn_gate_inp.weight") ||
-		t.name == "token_types.weight" {
-		// these tensors are always F32
+	if strings.HasSuffix(t.name, ".block_sparse_moe.gate.weight") {
 		return 0
 	}
 
@@ -45,9 +38,9 @@ func (t tensorBase) Kind() uint32 {
 	case 0:
 		panic("invalid tensor shape")
 	case 1:
-		return tensorKindF32
+		return 0
 	default:
-		return tensorKindF16
+		return 1
 	}
 }
 
@@ -57,25 +50,23 @@ func (t *tensorBase) SetRepacker(fn repacker) {
 
 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},
-		{"pytorch_model-*-of-*.bin", parseTorch},
-		{"pytorch_model.bin", parseTorch},
-		{"consolidated.*.pth", parseTorch},
+func parseTensors(d string) ([]Tensor, error) {
+	patterns := map[string]func(...string) ([]Tensor, error){
+		"model-*-of-*.safetensors": parseSafetensors,
+		"model.safetensors":        parseSafetensors,
+		"pytorch_model-*-of-*.bin": parseTorch,
+		"pytorch_model.bin":        parseTorch,
+		"consolidated.*.pth":       parseTorch,
 	}
 
-	for _, pattern := range patterns {
-		matches, err := fs.Glob(fsys, pattern.Pattern)
+	for pattern, parseFn := range patterns {
+		matches, err := filepath.Glob(filepath.Join(d, pattern))
 		if err != nil {
 			return nil, err
 		}
 
 		if len(matches) > 0 {
-			return pattern.Func(fsys, replacer, matches...)
+			return parseFn(matches...)
 		}
 	}
 

convert/reader_npz.go

@@ -0,0 +1,140 @@
+package convert
+
+import (
+	"encoding/binary"
+	"fmt"
+	"io"
+	"log/slog"
+	"strings"
+
+	"github.com/pdevine/tensor"
+	"github.com/pdevine/tensor/native"
+	"github.com/sbinet/npyio/npz"
+)
+
+type adapterTensor struct {
+	path  string
+	dtype string
+	*tensorBase
+}
+
+func DetectNPZ(fn string) (bool, error) {
+	f, err := npz.Open(fn)
+	if err != nil {
+		return false, err
+	}
+	defer f.Close()
+
+	if len(f.Keys()) > 0 && strings.HasSuffix(f.Keys()[0], ".npy") {
+		return true, nil
+	}
+
+	return false, nil
+}
+
+func parseNPZ(fn string) ([]Tensor, error) {
+	var ts []Tensor
+
+	f, err := npz.Open(fn)
+	if err != nil {
+		return nil, err
+	}
+	defer f.Close()
+
+	for _, name := range f.Keys() {
+		slog.Info(fmt.Sprintf("reading layer '%s'", name))
+		h := f.Header(name)
+
+		shape := make([]uint64, 2)
+		for cnt, v := range h.Descr.Shape {
+			// llamacpp expects the loraB layer to be reversed
+			if strings.Contains(name, "lora_b") {
+				shape[len(shape)-cnt-1] = uint64(v)
+			} else {
+				shape[cnt] = uint64(v)
+			}
+		}
+
+		dtypeMap := map[string]string{
+			"<f2": "F16",
+			"<f4": "F32",
+		}
+		dtype, ok := dtypeMap[h.Descr.Type]
+		if !ok {
+			return nil, fmt.Errorf("Unknown type '%s' for '%s'", h.Descr.Type, name)
+		}
+
+		ts = append(ts, adapterTensor{
+			path:  fn,
+			dtype: dtype,
+			tensorBase: &tensorBase{
+				name:  name,
+				shape: shape,
+			},
+		})
+	}
+	return ts, nil
+}
+
+func (t adapterTensor) Kind() uint32 {
+	switch t.dtype {
+	case "F32":
+		return 0
+	case "F16":
+		return 1
+	}
+	return 0
+}
+
+func (t adapterTensor) WriteTo(w io.Writer) (int64, error) {
+	f, err := npz.Open(t.path)
+	if err != nil {
+		return 0, err
+	}
+	defer f.Close()
+
+	switch t.dtype {
+	case "F32":
+		var f32s []float32
+		err = f.Read(t.tensorBase.name, &f32s)
+		if err != nil {
+			return 0, err
+		}
+
+		// ggla expects the loraB to be transposed
+		if strings.Contains(t.tensorBase.name, "lora_b") {
+			f32s, err = transpose(f32s, t.tensorBase.shape)
+			if err != nil {
+				return 0, err
+			}
+		}
+
+		return 0, binary.Write(w, binary.LittleEndian, f32s)
+	}
+
+	return 0, fmt.Errorf("unknown data type: %s", t.dtype)
+}
+
+func transpose(f32s []float32, shape []uint64) ([]float32, error) {
+	if len(shape) != 2 {
+		return nil, fmt.Errorf("only 2 dimensions supported for transpose")
+	}
+
+	// the shape is already backward
+	n := tensor.New(tensor.WithShape(int(shape[1]), int(shape[0])), tensor.WithBacking(f32s))
+	if err := n.T(1, 0); 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
+	}
+	f32s = make([]float32, 0)
+	for _, t := range ts {
+		f32s = append(f32s, t...)
+	}
+	return f32s, nil
+}

convert/reader_safetensors.go

@@ -4,12 +4,10 @@ import (
 	"bytes"
 	"encoding/binary"
 	"encoding/json"
-	"errors"
 	"fmt"
 	"io"
-	"io/fs"
+	"os"
 	"slices"
-	"strings"
 
 	"github.com/d4l3k/go-bfloat16"
 	"github.com/x448/float16"
@@ -22,10 +20,10 @@ type safetensorMetadata struct {
 	Offsets []int64  `json:"data_offsets"`
 }
 
-func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]Tensor, error) {
+func parseSafetensors(ps ...string) ([]Tensor, error) {
 	var ts []Tensor
 	for _, p := range ps {
-		f, err := fsys.Open(p)
+		f, err := os.Open(p)
 		if err != nil {
 			return nil, err
 		}
@@ -49,27 +47,15 @@ func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]T
 		keys := maps.Keys(headers)
 		slices.Sort(keys)
 
-		names := make(map[string]struct{}, len(keys))
-
 		for _, key := range keys {
 			if value := headers[key]; value.Type != "" {
-				// bitsandbytes quantized models are unsupported
-				if len(value.Shape) == 0 {
-					return nil, errors.New("unsupported safetensors model")
-				}
-				ggufName := replacer.Replace(key)
-				if _, ok := names[ggufName]; ok {
-					return nil, fmt.Errorf("duplicate tensor name '%s' was found for this model", ggufName)
-				}
-				names[ggufName] = struct{}{}
 				ts = append(ts, safetensor{
-					fs:     fsys,
 					path:   p,
 					dtype:  value.Type,
 					offset: safetensorsPad(n, value.Offsets[0]),
 					size:   safetensorsPad(n, value.Offsets[1]) - safetensorsPad(n, value.Offsets[0]),
 					tensorBase: &tensorBase{
-						name:  ggufName,
+						name:  key,
 						shape: value.Shape,
 					},
 				})
@@ -80,13 +66,11 @@ func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]T
 	return ts, nil
 }
 
-// safetensorsPad returns the padded size of the safetensors file given a length n and offset s
-func safetensorsPad(n, offset int64) int64 {
-	return 8 + n + offset
+func safetensorsPad(n, s int64) int64 {
+	return 8 + n + s
 }
 
 type safetensor struct {
-	fs     fs.FS
 	path   string
 	dtype  string
 	offset int64
@@ -95,20 +79,14 @@ type safetensor struct {
 }
 
 func (st safetensor) WriteTo(w io.Writer) (int64, error) {
-	f, err := st.fs.Open(st.path)
+	f, err := os.Open(st.path)
 	if err != nil {
 		return 0, err
 	}
 	defer f.Close()
 
-	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 = f.Seek(st.offset, io.SeekStart); err != nil {
+		return 0, err
 	}
 
 	var f32s []float32
@@ -124,9 +102,8 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 			return 0, err
 		}
 
-		f32s = make([]float32, len(u16s))
-		for i := range u16s {
-			f32s[i] = float16.Frombits(u16s[i]).Float32()
+		for _, b := range u16s {
+			f32s = append(f32s, float16.Frombits(b).Float32())
 		}
 
 	case "BF16":
@@ -148,9 +125,9 @@ func (st safetensor) WriteTo(w io.Writer) (int64, error) {
 	}
 
 	switch st.Kind() {
-	case tensorKindF32:
+	case 0:
 		return 0, binary.Write(w, binary.LittleEndian, f32s)
-	case tensorKindF16:
+	case 1:
 		f16s := make([]uint16, len(f32s))
 		for i := range f32s {
 			f16s[i] = float16.Fromfloat32(f32s[i]).Bits()

convert/reader_torch.go

@@ -2,14 +2,12 @@ package convert
 
 import (
 	"io"
-	"io/fs"
-	"strings"
 
 	"github.com/nlpodyssey/gopickle/pytorch"
 	"github.com/nlpodyssey/gopickle/types"
 )
 
-func parseTorch(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]Tensor, error) {
+func parseTorch(ps ...string) ([]Tensor, error) {
 	var ts []Tensor
 	for _, p := range ps {
 		pt, err := pytorch.Load(p)
@@ -28,7 +26,7 @@ func parseTorch(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]Tensor,
 			ts = append(ts, torch{
 				storage: t.(*pytorch.Tensor).Source,
 				tensorBase: &tensorBase{
-					name:  replacer.Replace(k.(string)),
+					name:  k.(string),
 					shape: shape,
 				},
 			})

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/testdata/Meta-Llama-3.1-8B-Instruct.json

@@ -1,3 +0,0 @@
-{
-  "rope_freqs.weight": "80fd5efb2f729381785b293a091a268cfeceb0079167f6ece9b07070e662b222"
-}

convert/testdata/Phi-3-mini-128k-instruct.json

@@ -1,225 +0,0 @@
-{
-  "general.architecture": "phi3",
-  "general.file_type": "1",
-  "general.quantization_version": "2",
-  "phi3.block_count": "32",
-  "phi3.context_length": "131072",
-  "phi3.embedding_length": "3072",
-  "phi3.feed_forward_length": "8192",
-  "phi3.rope.scaling.original_context_length": "4096",
-  "phi3.rope.dimension_count": "96",
-  "phi3.rope.freq_base": "10000",
-  "phi3.rope.scaling.attn_factor": "1.1902381",
-  "phi3.attention.head_count": "32",
-  "phi3.attention.head_count_kv": "32",
-  "phi3.attention.layer_norm_rms_epsilon": "1e-05",
-  "phi3.attention.sliding_window": "262144",
-  "tokenizer.ggml.model": "llama",
-  "tokenizer.ggml.pre": "default",
-  "tokenizer.ggml.add_bos_token": "false",
-  "tokenizer.ggml.add_eos_token": "false",
-  "tokenizer.ggml.bos_token_id": "1",
-  "tokenizer.ggml.eos_token_id": "32000",
-  "tokenizer.ggml.unknown_token_id": "0",
-  "tokenizer.ggml.padding_token_id": "32000",
-  "tokenizer.ggml.scores": "6e37bcde2adc7e350e87c496eddd7a2124329c1dc66c5bf3ad3997253e4f7a62",
-  "tokenizer.ggml.token_type": "b6ecf55ec64ee67d87750bdb8d757a2c58bf78377e9f4219f5689a6c4dea57ce",
-  "tokenizer.ggml.tokens": "d168da3ddd3eee820916945fcb9baf24dd3cde42f606cffa2d19e7c8a8743918",
-  "blk.0.attn_norm.weight": "216aeb2c9e0c271f899e1ef2a63cceeb8f41e97642e84fada54b1d3c1c11cf25",
-  "blk.0.attn_output.weight": "b597d56f7188ffc1fafc273fadc59d41738cffd677ae98c61a62c3285b3a3099",
-  "blk.0.attn_qkv.weight": "d28a6b44e13f59be5483e4be2bedb544e346168d720aca27f47d1a5a722be91e",
-  "blk.0.ffn_down.weight": "4a691370e5a61fcbbf540fbcbf4c0f1d15dec0364528c0e916d0744f6262b63b",
-  "blk.0.ffn_norm.weight": "0c00af2b4a3128bec64a0cbb1084b042fdbe13d9ad0d03bd577f9449dfead338",
-  "blk.0.ffn_up.weight": "b32b52f790c1c083bfb8a3126dc1111cfeeb28dc8c584a930a1e5334cb176bf4",
-  "blk.1.attn_norm.weight": "68748011503c6c029e8e69a84a8e5a89338f378769627b6dbf7f93d715c292e1",
-  "blk.1.attn_output.weight": "2267344add13b048ca59e4377c86dc512be8046a57156901fa32a20fa74e4ee0",
-  "blk.1.attn_qkv.weight": "9109d2e3d7a2eacfda5226587b8be124a3bf44b972da7ebb17aa15795897eacc",
-  "blk.1.ffn_down.weight": "d675df4df4dd039c0c339ad6445d39eddd2004db6bf35bed6314c7497245a633",
-  "blk.1.ffn_norm.weight": "3b5767ae977bc8baaa06b06efdbea193b6b3ba605ce76d77a76ce317e935500c",
-  "blk.1.ffn_up.weight": "80dfd6d9d234b00334c89b8e0a02f81899c2efd377321c34ba5ba51a5f61b5ff",
-  "blk.2.attn_norm.weight": "6a6743b057e5088f145bc179e92c9bfb41163e7295d7b81c62e23dd89d2b59c4",
-  "blk.2.attn_output.weight": "bc5491ea54e0db81462d7d9b7d25cbdda380c2db8de041bd1c4ab7b76a1d19c3",
-  "blk.2.attn_qkv.weight": "a61287a9852e2f5aca9c100b471d98398b2913a3497c743de3c70ec9ddd7087f",
-  "blk.2.ffn_down.weight": "4fddcc382c8dceeab027fe43d8d44e67edb5e8ce4b9a1b7f773c87770380ade1",
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convert/testdata/Qwen2.5-0.5B-Instruct.json

@@ -1,314 +0,0 @@
-{
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convert/testdata/all-MiniLM-L6-v2.json

@@ -1,124 +0,0 @@
-{
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convert/testdata/c4ai-command-r-v01.json

@@ -1,344 +0,0 @@
-{
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-}

convert/testdata/gemma-2-2b-it.json

@@ -1,312 +0,0 @@
-{
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-  "blk.18.post_attention_norm.weight": "a58dde3f12df3e94cbc27d87c8ea86f89af8a388a506446ff6758f05399b05fc",
-  "blk.18.post_ffw_norm.weight": "cebf90cc143577d483cca27b032dfd82031ee59bdf17c0e2cf60a0a3ad5bf996",
-  "blk.19.attn_k.weight": "4683375d0599ac9e2232196aae1e90af13a14cae26e865465de5c8e257bb2055",
-  "blk.19.attn_norm.weight": "f3eba936bfb1814bbcb0a1d62739eb66daac839df8c9c836fe0e94860df88525",
-  "blk.19.attn_output.weight": "51c0f01d38a9dcfe9bdbc4643576fab164c1d9e4b7168b7695c0ee55e6965667",
-  "blk.19.attn_q.weight": "28d15b69b8416f2e7ddc88fe381cb1e2ef2ad705fb1c268139ba96498cc74848",
-  "blk.19.attn_v.weight": "6860f1cd720638e63a981fa2c0b4db900129826bcb9823c9ddf9fb8b1b9f3383",
-  "blk.19.ffn_down.weight": "bc7f2d7827ee01c2dd41401c7b3b1700ad3a4ff620e8bb734f92630d342dcc7f",
-  "blk.19.ffn_gate.weight": "54d03ef69ba373fc410fbca8f1e34a565d58e4296d9a035ff7e48340b9c848e7",
-  "blk.19.ffn_norm.weight": "9178fc796a340ee6e8128ca74c0cb6203d1adbed6927af4e5ac7863da57affc7",
-  "blk.19.ffn_up.weight": "a77bd708026c6e83ad5c79c223278e74621bcf74a9641c7818d96b595daaad20",
-  "blk.19.post_attention_norm.weight": "ae94aa26f4c411bf9496a6fd4a6df64ee589ee1ae9a04b531d45acc95721e582",
-  "blk.19.post_ffw_norm.weight": "9ad210700edeef12133bdcff04bf1c7f62b49f6f4a9ba483c7cdc59857c24a5c",
-  "blk.20.attn_k.weight": "e35bce1e9f4a7a09ef34721f57ea38cfca68c272f52d923fe50af8308f66cfaa",
-  "blk.20.attn_norm.weight": "644800f6926fd34f233795c4dec1151a295d2138ca8cac33e3e48167d26f8b41",
-  "blk.20.attn_output.weight": "8d3758cd236471741e1ad66c0710cb79077dc8c7a3a292d35bc551c0c5abe627",
-  "blk.20.attn_q.weight": "c333b1f0f6f956b5d73891df10b1a0321e55fc31c40d623a24e1f52caa6a998b",
-  "blk.20.attn_v.weight": "8562b418d0c4868a050fb19fa3fcaf50a8cf1c669f537d666c80c7b3a04714e1",
-  "blk.20.ffn_down.weight": "97efb608ac44cc804198faec3ee66eafe56ced6b7ca5359700c6f1df75b7205e",
-  "blk.20.ffn_gate.weight": "5c61151d86f28415c73c73d90ec088c646cbe5c1640197caf58eb501ba7db293",
-  "blk.20.ffn_norm.weight": "24bbe0a701afd4bbeea65b3edde712b3cbb2281043bbc43dbf250582453116ed",
-  "blk.20.ffn_up.weight": "e170cf68e249566aa99eb6f6b265679bf9a5a6b76830ba24e7e130c2515910c4",
-  "blk.20.post_attention_norm.weight": "e092d751cfe20dbf2d348358f3b38397bd83e4ed94d6bbaa6bbaddcd902b2ac4",
-  "blk.20.post_ffw_norm.weight": "219a18a47dcba76e669e4322223a5a9227bd3db1de3fbd3d3cfb22e54a783c5a",
-  "blk.21.attn_k.weight": "c3a095ebddb42c63824f1c98da65263dc88e4d790a26aa1632840b44f5cc7cb1",
-  "blk.21.attn_norm.weight": "ef8bbaded5fbc45ad9cf3985ae02174524e7090fe6362811124f942ef643bec7",
-  "blk.21.attn_output.weight": "668f018aba72baac6252aa3ad58569ddd55ab751a0dd8d7bcc9fb9b6efb4bf53",
-  "blk.21.attn_q.weight": "e759c65663089f3bbbd51847934c185e680c82f1249065d5d487da638e519e6d",
-  "blk.21.attn_v.weight": "2ff57762686cf9ba1f5a6be76503454b97556ce67f4ac98254bd0562231197ba",
-  "blk.21.ffn_down.weight": "3fd106556fb721b1c28ae3f4026bc83eb1b08ed910f2ba5f466c6b5f327d91cb",
-  "blk.21.ffn_gate.weight": "338022d882f4b6619e8054a6fb909696fa3eef3013cf69b65c3cacdfc5b9e42c",
-  "blk.21.ffn_norm.weight": "1e77660c23a3f9653ee721a863d1960f773d87437cabc4dc0a6e17ee3d4e5e44",
-  "blk.21.ffn_up.weight": "7d31b20fbc2e6eba8f350f170069dc36f0cb12f68fbc4206ec5022a74085ebcb",
-  "blk.21.post_attention_norm.weight": "9638bae8d8bdcd7ed68da282979cd84a07c41ff9cabcaea94ebc846a1803db23",
-  "blk.21.post_ffw_norm.weight": "d622ef11115fe0cbe04b727d5a3b6371e7f39bf08c8d5eb9bc6da52e3f3cfb9d",
-  "blk.22.attn_k.weight": "5c321cb29deffbe57de200dd206a62005f1e80acb86c4fd2349dd44c8d3594fd",
-  "blk.22.attn_norm.weight": "198d949705d7170a331d75889d8c7500c3635254dac2cc6aa4dc35d556584536",
-  "blk.22.attn_output.weight": "19805cd5d7025b457e5d41d70db8b3fd63c2dd0e4a94d3ef1704d50ef4e749e8",
-  "blk.22.attn_q.weight": "177836cd583fc87405975ddc21ebfebdaa090a0363799664c72caa3da851ae2c",
-  "blk.22.attn_v.weight": "fea255692483e30d0108f9e4e250eb3ed7dbda8d83f499b06519b8c223ae6096",
-  "blk.22.ffn_down.weight": "00cb8939f03e5817d6d412de8cf2c923c9568d5493e382cec7faf5718fb034eb",
-  "blk.22.ffn_gate.weight": "b0591065b91281b2fbd8a9567f3568d40479f680e1f0a29e27ae213f37642489",
-  "blk.22.ffn_norm.weight": "96b5c5d0737c2ceb8fc869f54adb9e5f46e28cb7b177c40f49fa926b923c00f8",
-  "blk.22.ffn_up.weight": "81f472185b24344ab0594ea8246cc6e200e0dc1cab4943e74fbe4ca19d5a9701",
-  "blk.22.post_attention_norm.weight": "27fa9aa6260aa3071e0391e1a1d49322dcb6e8072315b8a9b7064087108dbd06",
-  "blk.22.post_ffw_norm.weight": "f37e1dcd7f643d9545675ffe9dc527a11eba86eb204989c2f44f636b266d896a",
-  "blk.23.attn_k.weight": "5d82f36658a56c3f94d0bb2d61f65509c966fa6568f81812e0d3e338b380ef8c",
-  "blk.23.attn_norm.weight": "b7983f88d9cad88bc88a528923e6da592ad20e699965b223ebc10840fe1f4fec",
-  "blk.23.attn_output.weight": "59f97f80f430d71606aab0158a195aed29ccd3405e6c0a5c41c809be8eb01898",
-  "blk.23.attn_q.weight": "53ac4789fe958919cc02ea4222bcd64c0ea1b4baa54304bff46635bdf42f7490",
-  "blk.23.attn_v.weight": "ec8abe09b9e84dbb52c7a068094657c6d3c62fe551ba8d7c3a3f23da622e9756",
-  "blk.23.ffn_down.weight": "3cf547eccb1b82aa64f208cee9682d7f558ca84e0aead7d9d3d1420d90f3d992",
-  "blk.23.ffn_gate.weight": "366aa2486d911ba81eb519119e13807deacf7e9908bc1975a2a63e00d6b10124",
-  "blk.23.ffn_norm.weight": "6d1d4a4af34bb7dc090ac87d6457d398c3e0fb68bd2e2b60b099dc318b6cfac3",
-  "blk.23.ffn_up.weight": "53f76692e253f5d2420b3f200c731b9f3b7a83e379920b4a067c729b4674aa4d",
-  "blk.23.post_attention_norm.weight": "7c952fa0efa76b3f048c8c4c9e8dcb5e3724d231327eda6423a34d3f3d3367de",
-  "blk.23.post_ffw_norm.weight": "7ab188cfe61f0a91b40309a0ab6bfa99f19d0ff2a37b6ac10e5f0c7f44eb5270",
-  "blk.24.attn_k.weight": "225798792f9bfdd10eff0505ebe61e0aad0209c17b431f6044ee7968ffe8c198",
-  "blk.24.attn_norm.weight": "635e3c1ebf5219bbebfc40ef164bc32d2b726ef595a94da64ac524ae878e2915",
-  "blk.24.attn_output.weight": "482f5bb2db8d9ed22b253d9a3296333b239efe698e5992e5d77e7e12dc2a5cf5",
-  "blk.24.attn_q.weight": "43805bbccddb65d58fffc4be9b5c374d4e1df1395ec1e1ffb4bcff03e98d5adb",
-  "blk.24.attn_v.weight": "fa741af54b4a3b1775d32f59134756090c5df2e7345a12a2d8db94fe289667a7",
-  "blk.24.ffn_down.weight": "83c6351e3162626b276f524a57836144625c2556dbe321b57cbd8fd486a68fab",
-  "blk.24.ffn_gate.weight": "fbe66be0d84d12cea5176cc7eaef64382ffc7324cd9d6266a3342dc43442f2ac",
-  "blk.24.ffn_norm.weight": "77c1445a8639ad24938bdf0280233eea2362d47391421833dfa72ec756dfc1e8",
-  "blk.24.ffn_up.weight": "78235ac729ee23c1cf1ae543751e3af32776d8808cee6e529c2a625a1f027654",
-  "blk.24.post_attention_norm.weight": "161f71b6d07628d43e4ae51a4c9088ec6ca2db123a17986a14505d83fdd04dad",
-  "blk.24.post_ffw_norm.weight": "cf1ba692aa683368b02ac413e69b2521b98c69a5274eacbb54165b53bf38a8b2",
-  "blk.25.attn_k.weight": "057a56bd8c8d2b41608d1f71faa3052902152ddf85e47669ad950c1c3e77c33f",
-  "blk.25.attn_norm.weight": "b7179fe02c334da556ddcf6c1b502245639a728c4cbba8b552d8e1df4565ee9d",
-  "blk.25.attn_output.weight": "4fed8b05b08a0ff75ffd022701bbeb52f17b23d09332a1ddcba737244bd0d3b0",
-  "blk.25.attn_q.weight": "c52e99f5d38bf7538d6106a0bbf38ac6dc6296bca9a3f849afa384ea67b4af01",
-  "blk.25.attn_v.weight": "c49c23d8e1cfa6a8eb971eb69942204890c6d7d830dc8774c84b108a80598912",
-  "blk.25.ffn_down.weight": "c08d4dc8412b19fdc870c164b83c341b236ec6fe7bb4a9bcfe0dc100faa20286",
-  "blk.25.ffn_gate.weight": "1a4cb3f36735d59181721471452807903006539e5e1b5ceb4f72d1d7ae134127",
-  "blk.25.ffn_norm.weight": "8fd6bd0dcec5198761525a36992a57c9ec5e9da60a22092839a84ae8c4e87f26",
-  "blk.25.ffn_up.weight": "3a00f39bdd5f31dc5e3b281d2002e1ac4f2475d49a0ac1d7720a25b377dcd04a",
-  "blk.25.post_attention_norm.weight": "e5f31a648612c859b6d21c9ee426e87a86cb1973dfdd86276c767371d9cef5ad",
-  "blk.25.post_ffw_norm.weight": "553c3bd774922c99c2384380a142d019881d30dbf0fe3bf9430dabfb3f6cbd33",
-  "output_norm.weight": "49445c4585ab0a8135717a0bdb1cda4a062a030177d0119561d91542aec5744b"
-}

convert/testdata/gemma-2-9b-it.json

@@ -1,6 +0,0 @@
-{
-  "general.architecture": "gemma2",
-  "gemma2.attention.sliding_window": "4096",
-  "gemma2.attn_logit_softcapping": "50",
-  "gemma2.final_logit_softcapping": "30"
-}

convert/tokenizer.go

@@ -1,18 +1,16 @@
 package convert
 
 import (
+	"cmp"
 	"crypto/sha256"
 	"encoding/hex"
 	"encoding/json"
 	"errors"
 	"fmt"
-	"io/fs"
 	"log/slog"
 	"os"
+	"path/filepath"
 	"slices"
-	"strings"
-
-	"golang.org/x/exp/maps"
 )
 
 const (
@@ -34,8 +32,8 @@ type Tokenizer struct {
 	Template string
 }
 
-func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error) {
-	v, err := parseVocabulary(fsys)
+func parseTokenizer(d string, specialTypes []string) (*Tokenizer, error) {
+	v, err := parseVocabulary(d)
 	if err != nil {
 		return nil, err
 	}
@@ -46,7 +44,7 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 	}
 
 	addedTokens := make(map[string]token)
-	if f, err := fsys.Open("tokenizer.json"); errors.Is(err, os.ErrNotExist) {
+	if f, err := os.Open(filepath.Join(d, "tokenizer.json")); errors.Is(err, os.ErrNotExist) {
 	} else if err != nil {
 		return nil, err
 	} else {
@@ -61,33 +59,13 @@ 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 {
 			switch pt.Type {
 			case "Split":
 				if pt.Pattern.Regex != "" {
-					// create a checksum of all Split pretokenizers which should be sufficient
-					// to identify the pretokenizer
 					sha256sum.Write([]byte(pt.Pattern.Regex))
 				}
 			}
@@ -100,8 +78,6 @@ 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 +85,7 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 		}
 	}
 
-	if f, err := fsys.Open("tokenizer_config.json"); errors.Is(err, os.ErrNotExist) {
+	if f, err := os.Open(filepath.Join(d, "tokenizer_config.json")); errors.Is(err, os.ErrNotExist) {
 	} else if err != nil {
 		return nil, err
 	} else {
@@ -121,25 +97,12 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 		}
 
 		if template, ok := p["chat_template"]; ok {
-			var s []struct {
-				Name     string `json:"name"`
-				Template string `json:"template"`
-			}
-			if err := json.Unmarshal(template, &t.Template); err == nil {
-				// noop
-			} else if err := json.Unmarshal(template, &s); err == nil {
-				for _, e := range s {
-					if e.Name == "default" {
-						t.Template = e.Template
-						break
-					}
-				}
-			} else {
-				return nil, fmt.Errorf("invalid chat_template: %w", err)
+			if err := json.Unmarshal(template, &t.Template); err != nil {
+				return nil, err
 			}
 		}
 
-		for _, st := range specialTokenTypes {
+		for _, st := range specialTypes {
 			sv := SpecialVocabulary{Type: st}
 			if bts, ok := p[fmt.Sprintf("add_%s_token", st)]; ok {
 				if err := json.Unmarshal(bts, &sv.AddToken); err != nil {
@@ -175,11 +138,12 @@ func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error)
 }
 
 type tokenizer struct {
+	Version     string  `json:"version"`
 	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 {
@@ -206,8 +170,8 @@ type Vocabulary struct {
 	Types  []int32
 }
 
-func parseVocabularyFromTokenizer(fsys fs.FS) (*Vocabulary, error) {
-	f, err := fsys.Open("tokenizer.json")
+func parseVocabularyFromTokenizer(p string) (*Vocabulary, error) {
+	f, err := os.Open(filepath.Join(p, "tokenizer.json"))
 	if err != nil {
 		return nil, err
 	}
@@ -218,32 +182,32 @@ func parseVocabularyFromTokenizer(fsys fs.FS) (*Vocabulary, error) {
 		return nil, err
 	}
 
-	tokens := make(map[int]token, len(t.Model.Vocab))
+	var tokens []token
 	for k, v := range t.Model.Vocab {
-		tokens[v] = token{
+		tokens = append(tokens, token{
 			ID:      v,
 			Content: k,
-		}
+		})
 	}
 
-	for _, token := range t.AddedTokens {
-		token.UserDefined = true
-		tokens[token.ID] = token
+	for _, t := range t.AddedTokens {
+		t.UserDefined = true
+		tokens = append(tokens, t)
 	}
 
-	keys := maps.Keys(tokens)
-	slices.Sort(keys)
+	slices.SortFunc(tokens, func(i, j token) int {
+		return cmp.Compare(i.ID, j.ID)
+	})
 
 	v := Vocabulary{Model: "gpt2"}
-	for _, k := range keys {
-		token := tokens[k]
-		v.Tokens = append(v.Tokens, token.Content)
-		v.Scores = append(v.Scores, float32(token.ID))
+	for _, t := range tokens {
+		v.Tokens = append(v.Tokens, t.Content)
+		v.Scores = append(v.Scores, float32(t.ID))
 
 		switch {
-		case token.Special:
+		case t.Special:
 			v.Types = append(v.Types, tokenTypeControl)
-		case token.UserDefined:
+		case t.UserDefined:
 			v.Types = append(v.Types, tokenTypeUserDefined)
 		default:
 			v.Types = append(v.Types, tokenTypeNormal)
@@ -253,26 +217,24 @@ func parseVocabularyFromTokenizer(fsys fs.FS) (*Vocabulary, error) {
 	return &v, nil
 }
 
-func parseVocabulary(fsys fs.FS) (*Vocabulary, error) {
-	patterns := []struct {
-		Pattern string
-		Func    func(fs.FS) (*Vocabulary, error)
-	}{
-		{"tokenizer.model", parseSentencePiece},
-		{"tokenizer.json", parseVocabularyFromTokenizer},
+func parseVocabulary(d string) (*Vocabulary, error) {
+	patterns := map[string]func(string) (*Vocabulary, error){
+		"tokenizer.model": parseSentencePiece,
+		"tokenizer.json":  parseVocabularyFromTokenizer,
 	}
 
-	for _, pattern := range patterns {
-		if _, err := fs.Stat(fsys, pattern.Pattern); errors.Is(err, os.ErrNotExist) {
-			continue
-		} else if err != nil {
+	for pattern, parseFn := range patterns {
+		matches, err := filepath.Glob(filepath.Join(d, pattern))
+		if err != nil {
 			return nil, err
 		}
 
-		return pattern.Func(fsys)
+		if len(matches) > 0 {
+			return parseFn(d)
+		}
 	}
 
-	return nil, errors.New("unknown tokenizer format")
+	return nil, errors.New("unknown tensor format")
 }
 
 type SpecialVocabulary struct {

convert/tokenizer_spm.go

@@ -5,10 +5,8 @@ import (
 	"encoding/json"
 	"errors"
 	"fmt"
-	"io/fs"
-	"log/slog"
 	"os"
-	"reflect"
+	"path/filepath"
 	"slices"
 
 	"google.golang.org/protobuf/proto"
@@ -16,15 +14,8 @@ import (
 	"github.com/ollama/ollama/convert/sentencepiece"
 )
 
-func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
-	slog.Debug("using spm vocabulary")
-
-	ast, err := parseAdditionalSpecialTokens(fsys)
-	if err != nil {
-		return nil, err
-	}
-
-	bts, err := fs.ReadFile(fsys, "tokenizer.model")
+func parseSentencePiece(d string) (*Vocabulary, error) {
+	bts, err := os.ReadFile(filepath.Join(d, "tokenizer.model"))
 	if err != nil {
 		return nil, err
 	}
@@ -46,25 +37,11 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 			sentencepiece.ModelProto_SentencePiece_BYTE:
 			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()) {
-				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)
+			v.Types = append(v.Types, int32(sentencepiece.ModelProto_SentencePiece_NORMAL))
 		}
 	}
 
-	f, err := fsys.Open("added_tokens.json")
+	f, err := os.Open(filepath.Join(d, "added_tokens.json"))
 	if errors.Is(err, os.ErrNotExist) {
 		return &v, nil
 	} else if err != nil {
@@ -91,16 +68,10 @@ 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)
@@ -110,62 +81,3 @@ 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) {
-	f, err := fsys.Open("special_tokens_map.json")
-	if errors.Is(err, os.ErrNotExist) {
-		return nil, nil
-	} else if err != nil {
-		return nil, err
-	}
-	defer f.Close()
-
-	var m struct {
-		AdditionalSpecialTokens any `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
-}

convert/tokenizer_test.go

@@ -1,264 +0,0 @@
-package convert
-
-import (
-	"io"
-	"io/fs"
-	"os"
-	"path/filepath"
-	"strings"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-)
-
-func createTokenizerFS(t *testing.T, dir string, files map[string]io.Reader) fs.FS {
-	t.Helper()
-
-	for k, v := range files {
-		if err := func() error {
-			f, err := os.Create(filepath.Join(dir, k))
-			if err != nil {
-				return err
-			}
-			defer f.Close()
-
-			if _, err := io.Copy(f, v); err != nil {
-				return err
-			}
-
-			return nil
-		}(); err != nil {
-			t.Fatalf("unexpected error: %v", err)
-		}
-	}
-
-	return os.DirFS(dir)
-}
-
-func TestParseTokenizer(t *testing.T) {
-	cases := []struct {
-		name              string
-		fsys              fs.FS
-		specialTokenTypes []string
-		want              *Tokenizer
-	}{
-		{
-			name: "string chat template",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{}`),
-				"tokenizer_config.json": strings.NewReader(`{
-					"chat_template": "<default template>"
-				}`),
-			}),
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{Model: "gpt2"},
-				Pre:        "default",
-				Template:   "<default template>",
-			},
-		},
-		{
-			name: "list chat template",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{}`),
-				"tokenizer_config.json": strings.NewReader(`{
-					"chat_template": [
-						{
-							"name": "default",
-							"template": "<default template>"
-						},
-						{
-							"name": "tools",
-							"template": "<tools template>"
-						}
-					]
-				}`),
-			}),
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{Model: "gpt2"},
-				Pre:        "default",
-				Template:   "<default template>",
-			},
-		},
-		{
-			name: "added tokens",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{
-					"added_tokens": [
-						{
-							"id": 999,
-							"content": "<unused999>",
-							"special": false
-						}
-					]
-				}`),
-			}),
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{
-					Model:  "gpt2",
-					Tokens: []string{"<unused999>"},
-					Scores: []float32{999},
-					Types:  []int32{4},
-				},
-				Pre: "default",
-			},
-		},
-		{
-			name: "added tokens overlap vocab",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{
-					"added_tokens": [
-						{
-							"id": 0,
-							"content": "<pad>",
-							"special": true
-						}
-					],
-					"model": {
-						"vocab": {
-							"<pad>": 0
-						}
-					}
-				}`),
-			}),
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{
-					Model:  "gpt2",
-					Tokens: []string{"<pad>"},
-					Scores: []float32{0},
-					Types:  []int32{3},
-				},
-				Pre: "default",
-			},
-		},
-		{
-			name: "special token types",
-			fsys: createTokenizerFS(t, t.TempDir(), map[string]io.Reader{
-				"tokenizer.json": strings.NewReader(`{
-					"added_tokens": [
-						{
-							"id": 0,
-							"content": "<pad>",
-							"special": true
-						},
-						{
-							"id": 1,
-							"content": "<eos>",
-							"special": true
-						},
-						{
-							"id": 2,
-							"content": "<bos>",
-							"special": true
-						},
-						{
-							"id": 3,
-							"content": "<unk>",
-							"special": true
-						}
-					],
-					"model": {
-						"vocab": {
-							"<pad>": 0,
-							"<eos>": 1,
-							"<bos>": 2,
-							"<unk>": 3
-						}
-					}
-				}`),
-				"tokenizer_config.json": strings.NewReader(`{
-					"add_bos_token": true,
-					"add_eos_token": false,
-					"bos_token": "<bos>",
-					"eos_token": "<eos>",
-					"pad_token": "<pad>",
-					"unk_token": "<unk>"
-				}`),
-			}),
-			specialTokenTypes: []string{"pad", "eos", "bos", "unk"},
-			want: &Tokenizer{
-				Vocabulary: &Vocabulary{
-					Model:  "gpt2",
-					Tokens: []string{"<pad>", "<eos>", "<bos>", "<unk>"},
-					Scores: []float32{0, 1, 2, 3},
-					Types:  []int32{3, 3, 3, 3},
-				},
-				SpecialVocabulary: []*SpecialVocabulary{
-					{Type: "pad", Content: "<pad>", ID: 0, AddToken: false},
-					{Type: "eos", Content: "<eos>", ID: 1, AddToken: false},
-					{Type: "bos", Content: "<bos>", ID: 2, AddToken: true},
-					{Type: "unk", Content: "<unk>", ID: 3, AddToken: false},
-				},
-				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",
-			},
-		},
-	}
-
-	for _, tt := range cases {
-		t.Run(tt.name, func(t *testing.T) {
-			tokenizer, err := parseTokenizer(tt.fsys, tt.specialTokenTypes)
-			if err != nil {
-				t.Fatalf("unexpected error: %v", err)
-			}
-
-			if diff := cmp.Diff(tt.want, tokenizer); diff != "" {
-				t.Errorf("unexpected tokenizer (-want +got):\n%s", diff)
-			}
-		})
-	}
-}

discover/cpu_common.go

@@ -1,24 +0,0 @@
-package discover
-
-import (
-	"os"
-	"path/filepath"
-	"runtime"
-	"strings"
-)
-
-func IsNUMA() bool {
-	if runtime.GOOS != "linux" {
-		// numa support in llama.cpp is linux only
-		return false
-	}
-	ids := map[string]any{}
-	packageIds, _ := filepath.Glob("/sys/devices/system/cpu/cpu*/topology/physical_package_id")
-	for _, packageId := range packageIds {
-		id, err := os.ReadFile(packageId)
-		if err == nil {
-			ids[strings.TrimSpace(string(id))] = struct{}{}
-		}
-	}
-	return len(ids) > 1
-}

discover/cuda_common.go

@@ -1,65 +0,0 @@
-//go:build linux || windows
-
-package discover
-
-import (
-	"log/slog"
-	"os"
-	"regexp"
-	"runtime"
-	"strconv"
-	"strings"
-)
-
-// Jetson devices have JETSON_JETPACK="x.y.z" factory set to the Jetpack version installed.
-// 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 != "" {
-			ver := strings.Split(CudaTegra, ".")
-			if len(ver) > 0 {
-				return "jetpack" + ver[0]
-			}
-		} else if data, err := os.ReadFile("/etc/nv_tegra_release"); err == nil {
-			r := regexp.MustCompile(` R(\d+) `)
-			m := r.FindSubmatch(data)
-			if len(m) != 2 {
-				slog.Info("Unexpected format for /etc/nv_tegra_release.  Set JETSON_JETPACK to select version")
-			} else {
-				if l4t, err := strconv.Atoi(string(m[1])); err == nil {
-					// Note: mapping from L4t -> JP is inconsistent (can't just subtract 30)
-					// https://developer.nvidia.com/embedded/jetpack-archive
-					switch l4t {
-					case 35:
-						return "jetpack5"
-					case 36:
-						return "jetpack6"
-					default:
-						slog.Info("unsupported L4T version", "nv_tegra_release", string(data))
-					}
-				}
-			}
-		}
-	}
-
-	// driver 12.0 has problems with the cuda v12 library, so run v11 on those older drivers
-	if gpuInfo.DriverMajor < 12 || (gpuInfo.DriverMajor == 12 && gpuInfo.DriverMinor == 0) {
-		return "v11"
-	}
-	return "v12"
-}

discover/gpu_linux.go

@@ -1,198 +0,0 @@
-package discover
-
-import (
-	"bufio"
-	"fmt"
-	"io"
-	"os"
-	"reflect"
-	"regexp"
-	"sort"
-	"strings"
-
-	"github.com/ollama/ollama/format"
-)
-
-var CudartGlobs = []string{
-	"/usr/local/cuda/lib64/libcudart.so*",
-	"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
-	"/usr/lib/x86_64-linux-gnu/libcudart.so*",
-	"/usr/lib/wsl/lib/libcudart.so*",
-	"/usr/lib/wsl/drivers/*/libcudart.so*",
-	"/opt/cuda/lib64/libcudart.so*",
-	"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
-	"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
-	"/usr/lib/aarch64-linux-gnu/libcudart.so*",
-	"/usr/local/cuda/lib*/libcudart.so*",
-	"/usr/lib*/libcudart.so*",
-	"/usr/local/lib*/libcudart.so*",
-}
-
-var NvmlGlobs = []string{}
-
-var NvcudaGlobs = []string{
-	"/usr/local/cuda*/targets/*/lib/libcuda.so*",
-	"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
-	"/usr/lib/*-linux-gnu/libcuda.so*",
-	"/usr/lib/wsl/lib/libcuda.so*",
-	"/usr/lib/wsl/drivers/*/libcuda.so*",
-	"/opt/cuda/lib*/libcuda.so*",
-	"/usr/local/cuda/lib*/libcuda.so*",
-	"/usr/lib*/libcuda.so*",
-	"/usr/local/lib*/libcuda.so*",
-}
-
-var OneapiGlobs = []string{
-	"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
-	"/usr/lib*/libze_intel_gpu.so*",
-}
-
-var (
-	CudartMgmtName = "libcudart.so*"
-	NvcudaMgmtName = "libcuda.so*"
-	NvmlMgmtName   = "" // not currently wired on linux
-	OneapiMgmtName = "libze_intel_gpu.so*"
-)
-
-func GetCPUMem() (memInfo, error) {
-	var mem memInfo
-	var total, available, free, buffers, cached, freeSwap uint64
-	f, err := os.Open("/proc/meminfo")
-	if err != nil {
-		return mem, err
-	}
-	defer f.Close()
-	s := bufio.NewScanner(f)
-	for s.Scan() {
-		line := s.Text()
-		switch {
-		case strings.HasPrefix(line, "MemTotal:"):
-			_, err = fmt.Sscanf(line, "MemTotal:%d", &total)
-		case strings.HasPrefix(line, "MemAvailable:"):
-			_, err = fmt.Sscanf(line, "MemAvailable:%d", &available)
-		case strings.HasPrefix(line, "MemFree:"):
-			_, err = fmt.Sscanf(line, "MemFree:%d", &free)
-		case strings.HasPrefix(line, "Buffers:"):
-			_, err = fmt.Sscanf(line, "Buffers:%d", &buffers)
-		case strings.HasPrefix(line, "Cached:"):
-			_, err = fmt.Sscanf(line, "Cached:%d", &cached)
-		case strings.HasPrefix(line, "SwapFree:"):
-			_, err = fmt.Sscanf(line, "SwapFree:%d", &freeSwap)
-		default:
-			continue
-		}
-		if err != nil {
-			return mem, err
-		}
-	}
-	mem.TotalMemory = total * format.KibiByte
-	mem.FreeSwap = freeSwap * format.KibiByte
-	if available > 0 {
-		mem.FreeMemory = available * format.KibiByte
-	} else {
-		mem.FreeMemory = (free + buffers + cached) * format.KibiByte
-	}
-	return mem, nil
-}
-
-const CpuInfoFilename = "/proc/cpuinfo"
-
-type linuxCpuInfo struct {
-	ID         string `cpuinfo:"processor"`
-	VendorID   string `cpuinfo:"vendor_id"`
-	ModelName  string `cpuinfo:"model name"`
-	PhysicalID string `cpuinfo:"physical id"`
-	Siblings   string `cpuinfo:"siblings"`
-	CoreID     string `cpuinfo:"core id"`
-}
-
-func GetCPUDetails() ([]CPU, error) {
-	file, err := os.Open(CpuInfoFilename)
-	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{}
-	cpu := &linuxCpuInfo{}
-	for scanner.Scan() {
-		line := scanner.Text()
-		if sl := reColumns.Split(line, 2); len(sl) > 1 {
-			t := reflect.TypeOf(cpu).Elem()
-			s := reflect.ValueOf(cpu).Elem()
-			for i := range t.NumField() {
-				field := t.Field(i)
-				tag := field.Tag.Get("cpuinfo")
-				if tag == sl[0] {
-					s.FieldByName(field.Name).SetString(sl[1])
-					break
-				}
-			}
-		} else if strings.TrimSpace(line) == "" && cpu.ID != "" {
-			cpuInfos = append(cpuInfos, *cpu)
-			cpu = &linuxCpuInfo{}
-		}
-	}
-	if cpu.ID != "" {
-		cpuInfos = append(cpuInfos, *cpu)
-	}
-
-	// Process the sockets/cores/threads
-	socketByID := map[string]*CPU{}
-	coreBySocket := map[string]map[string]struct{}{}
-	threadsByCoreBySocket := map[string]map[string]int{}
-	for _, c := range cpuInfos {
-		if _, found := socketByID[c.PhysicalID]; !found {
-			socketByID[c.PhysicalID] = &CPU{
-				ID:        c.PhysicalID,
-				VendorID:  c.VendorID,
-				ModelName: c.ModelName,
-			}
-			coreBySocket[c.PhysicalID] = map[string]struct{}{}
-			threadsByCoreBySocket[c.PhysicalID] = map[string]int{}
-		}
-		if c.CoreID != "" {
-			coreBySocket[c.PhysicalID][c.PhysicalID+":"+c.CoreID] = struct{}{}
-			threadsByCoreBySocket[c.PhysicalID][c.PhysicalID+":"+c.CoreID]++
-		} else {
-			coreBySocket[c.PhysicalID][c.PhysicalID+":"+c.ID] = struct{}{}
-			threadsByCoreBySocket[c.PhysicalID][c.PhysicalID+":"+c.ID]++
-		}
-	}
-
-	// Tally up the values from the tracking maps
-	for id, s := range socketByID {
-		s.CoreCount = len(coreBySocket[id])
-		s.ThreadCount = 0
-
-		// 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++
-			}
-		}
-		if efficiencyCoreCount == s.CoreCount {
-			// 1:1 mapping means they're not actually efficiency cores, but regular cores
-			s.EfficiencyCoreCount = 0
-		} else {
-			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])
-	}
-	return result, nil
-}

discover/gpu_test.go

@@ -1,60 +0,0 @@
-package discover
-
-import (
-	"runtime"
-	"testing"
-
-	"github.com/stretchr/testify/assert"
-	"github.com/stretchr/testify/require"
-)
-
-func TestBasicGetGPUInfo(t *testing.T) {
-	info := GetGPUInfo()
-	assert.NotEmpty(t, len(info))
-	assert.Contains(t, "cuda rocm cpu metal", info[0].Library)
-	if info[0].Library != "cpu" {
-		assert.Greater(t, info[0].TotalMemory, uint64(0))
-		assert.Greater(t, info[0].FreeMemory, uint64(0))
-	}
-}
-
-func TestCPUMemInfo(t *testing.T) {
-	info, err := GetCPUMem()
-	require.NoError(t, err)
-	switch runtime.GOOS {
-	case "darwin":
-		t.Skip("CPU memory not populated on darwin")
-	case "linux", "windows":
-		assert.Greater(t, info.TotalMemory, uint64(0))
-		assert.Greater(t, info.FreeMemory, uint64(0))
-	default:
-		return
-	}
-}
-
-func TestByLibrary(t *testing.T) {
-	type testCase struct {
-		input  []GpuInfo
-		expect int
-	}
-
-	testCases := map[string]*testCase{
-		"empty":                    {input: []GpuInfo{}, expect: 0},
-		"cpu":                      {input: []GpuInfo{{Library: "cpu"}}, expect: 1},
-		"cpu + GPU":                {input: []GpuInfo{{Library: "cpu"}, {Library: "cuda"}}, expect: 2},
-		"cpu + 2 GPU no variant":   {input: []GpuInfo{{Library: "cpu"}, {Library: "cuda"}, {Library: "cuda"}}, expect: 2},
-		"cpu + 2 GPU same variant": {input: []GpuInfo{{Library: "cpu"}, {Library: "cuda", Variant: "v11"}, {Library: "cuda", Variant: "v11"}}, expect: 2},
-		"cpu + 2 GPU diff variant": {input: []GpuInfo{{Library: "cpu"}, {Library: "cuda", Variant: "v11"}, {Library: "cuda", Variant: "v12"}}, expect: 3},
-	}
-
-	for k, v := range testCases {
-		t.Run(k, func(t *testing.T) {
-			resp := (GpuInfoList)(v.input).ByLibrary()
-			if len(resp) != v.expect {
-				t.Fatalf("expected length %d, got %d => %+v", v.expect, len(resp), resp)
-			}
-		})
-	}
-}
-
-// TODO - add some logic to figure out card type through other means and actually verify we got back what we expected

discover/gpu_windows.go

@@ -1,234 +0,0 @@
-package discover
-
-import (
-	"fmt"
-	"log/slog"
-	"syscall"
-	"unsafe"
-)
-
-type MEMORYSTATUSEX struct {
-	length               uint32
-	MemoryLoad           uint32
-	TotalPhys            uint64
-	AvailPhys            uint64
-	TotalPageFile        uint64
-	AvailPageFile        uint64
-	TotalVirtual         uint64
-	AvailVirtual         uint64
-	AvailExtendedVirtual uint64
-}
-
-var (
-	k32                              = syscall.NewLazyDLL("kernel32.dll")
-	globalMemoryStatusExProc         = k32.NewProc("GlobalMemoryStatusEx")
-	sizeofMemoryStatusEx             = uint32(unsafe.Sizeof(MEMORYSTATUSEX{}))
-	GetLogicalProcessorInformationEx = k32.NewProc("GetLogicalProcessorInformationEx")
-)
-
-var CudartGlobs = []string{
-	"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
-}
-
-var NvmlGlobs = []string{
-	"c:\\Windows\\System32\\nvml.dll",
-}
-
-var NvcudaGlobs = []string{
-	"c:\\windows\\system*\\nvcuda.dll",
-}
-
-var OneapiGlobs = []string{
-	"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
-}
-
-var (
-	CudartMgmtName = "cudart64_*.dll"
-	NvcudaMgmtName = "nvcuda.dll"
-	NvmlMgmtName   = "nvml.dll"
-	OneapiMgmtName = "ze_intel_gpu64.dll"
-)
-
-func GetCPUMem() (memInfo, error) {
-	memStatus := MEMORYSTATUSEX{length: sizeofMemoryStatusEx}
-	r1, _, err := globalMemoryStatusExProc.Call(uintptr(unsafe.Pointer(&memStatus)))
-	if r1 == 0 {
-		return memInfo{}, fmt.Errorf("GlobalMemoryStatusEx failed: %w", err)
-	}
-	return memInfo{TotalMemory: memStatus.TotalPhys, FreeMemory: memStatus.AvailPhys, FreeSwap: memStatus.AvailPageFile}, nil
-}
-
-type LOGICAL_PROCESSOR_RELATIONSHIP uint32
-
-const (
-	RelationProcessorCore LOGICAL_PROCESSOR_RELATIONSHIP = iota
-	RelationNumaNode
-	RelationCache
-	RelationProcessorPackage
-	RelationGroup
-	RelationProcessorDie
-	RelationNumaNodeEx
-	RelationProcessorModule
-)
-const RelationAll LOGICAL_PROCESSOR_RELATIONSHIP = 0xffff
-
-type GROUP_AFFINITY struct {
-	Mask     uintptr // KAFFINITY
-	Group    uint16
-	Reserved [3]uint16
-}
-
-type PROCESSOR_RELATIONSHIP struct {
-	Flags           byte
-	EfficiencyClass byte
-	Reserved        [20]byte
-	GroupCount      uint16
-	GroupMask       [1]GROUP_AFFINITY // len GroupCount
-}
-
-// Omitted unused structs: NUMA_NODE_RELATIONSHIP CACHE_RELATIONSHIP GROUP_RELATIONSHIP
-
-type SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX struct {
-	Relationship LOGICAL_PROCESSOR_RELATIONSHIP
-	Size         uint32
-	U            [1]byte // Union len Size
-	// PROCESSOR_RELATIONSHIP
-	// NUMA_NODE_RELATIONSHIP
-	// CACHE_RELATIONSHIP
-	// GROUP_RELATIONSHIP
-}
-
-func (group *GROUP_AFFINITY) IsMember(target *GROUP_AFFINITY) bool {
-	if group == nil || target == nil {
-		return false
-	}
-	return group.Mask&target.Mask != 0
-}
-
-type winPackage struct {
-	groups              []*GROUP_AFFINITY
-	coreCount           int // performance cores = coreCount - efficiencyCoreCount
-	efficiencyCoreCount int
-	threadCount         int
-}
-
-func (pkg *winPackage) IsMember(target *GROUP_AFFINITY) bool {
-	for _, group := range pkg.groups {
-		if group.IsMember(target) {
-			return true
-		}
-	}
-	return false
-}
-
-func getLogicalProcessorInformationEx() ([]byte, error) {
-	buf := make([]byte, 1)
-	bufSize := len(buf)
-	ret, _, err := GetLogicalProcessorInformationEx.Call(
-		uintptr(RelationAll),
-		uintptr(unsafe.Pointer(&buf[0])),
-		uintptr(unsafe.Pointer(&bufSize)),
-	)
-	if ret != 0 {
-		return nil, fmt.Errorf("failed to determine size info ret:%d %w", ret, err)
-	}
-
-	buf = make([]byte, bufSize)
-	ret, _, err = GetLogicalProcessorInformationEx.Call(
-		uintptr(RelationAll),
-		uintptr(unsafe.Pointer(&buf[0])),
-		uintptr(unsafe.Pointer(&bufSize)),
-	)
-	if ret == 0 {
-		return nil, fmt.Errorf("failed to gather processor information ret:%d buflen:%d %w", ret, bufSize, err)
-	}
-	return buf, nil
-}
-
-func processSystemLogicalProcessorInforationList(buf []byte) []*winPackage {
-	var slpi *SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX
-	// Find all the packages first
-	packages := []*winPackage{}
-	for bufOffset := 0; bufOffset < len(buf); bufOffset += int(slpi.Size) {
-		slpi = (*SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX)(unsafe.Pointer(&buf[bufOffset]))
-		if slpi.Relationship != RelationProcessorPackage {
-			continue
-		}
-		pr := (*PROCESSOR_RELATIONSHIP)(unsafe.Pointer(&slpi.U[0]))
-		pkg := &winPackage{}
-		ga0 := unsafe.Pointer(&pr.GroupMask[0])
-		for j := range pr.GroupCount {
-			gm := (*GROUP_AFFINITY)(unsafe.Pointer(uintptr(ga0) + uintptr(j)*unsafe.Sizeof(GROUP_AFFINITY{})))
-			pkg.groups = append(pkg.groups, gm)
-		}
-		packages = append(packages, pkg)
-	}
-
-	slog.Info("packages", "count", len(packages))
-
-	// To identify efficiency cores we have to compare the relative values
-	// Larger values are "less efficient" (aka, more performant)
-	var maxEfficiencyClass byte
-	for bufOffset := 0; bufOffset < len(buf); bufOffset += int(slpi.Size) {
-		slpi = (*SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX)(unsafe.Pointer(&buf[bufOffset]))
-		if slpi.Relationship != RelationProcessorCore {
-			continue
-		}
-		pr := (*PROCESSOR_RELATIONSHIP)(unsafe.Pointer(&slpi.U[0]))
-		if pr.EfficiencyClass > maxEfficiencyClass {
-			maxEfficiencyClass = pr.EfficiencyClass
-		}
-	}
-	if maxEfficiencyClass > 0 {
-		slog.Info("efficiency cores detected", "maxEfficiencyClass", maxEfficiencyClass)
-	}
-
-	// then match up the Cores to the Packages, count up cores, threads and efficiency cores
-	for bufOffset := 0; bufOffset < len(buf); bufOffset += int(slpi.Size) {
-		slpi = (*SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX)(unsafe.Pointer(&buf[bufOffset]))
-		if slpi.Relationship != RelationProcessorCore {
-			continue
-		}
-		pr := (*PROCESSOR_RELATIONSHIP)(unsafe.Pointer(&slpi.U[0]))
-		ga0 := unsafe.Pointer(&pr.GroupMask[0])
-		for j := range pr.GroupCount {
-			gm := (*GROUP_AFFINITY)(unsafe.Pointer(uintptr(ga0) + uintptr(j)*unsafe.Sizeof(GROUP_AFFINITY{})))
-			for _, pkg := range packages {
-				if pkg.IsMember(gm) {
-					pkg.coreCount++
-					if pr.Flags == 0 {
-						pkg.threadCount++
-					} else {
-						pkg.threadCount += 2
-					}
-					if pr.EfficiencyClass < maxEfficiencyClass {
-						pkg.efficiencyCoreCount++
-					}
-				}
-			}
-		}
-	}
-
-	// Summarize the results
-	for i, pkg := range packages {
-		slog.Info("", "package", i, "cores", pkg.coreCount, "efficiency", pkg.efficiencyCoreCount, "threads", pkg.threadCount)
-	}
-
-	return packages
-}
-
-func GetCPUDetails() ([]CPU, error) {
-	buf, err := getLogicalProcessorInformationEx()
-	if err != nil {
-		return nil, err
-	}
-	packages := processSystemLogicalProcessorInforationList(buf)
-	cpus := make([]CPU, len(packages))
-
-	for i, pkg := range packages {
-		cpus[i].CoreCount = pkg.coreCount
-		cpus[i].EfficiencyCoreCount = pkg.efficiencyCoreCount
-		cpus[i].ThreadCount = pkg.threadCount
-	}
-	return cpus, nil
-}

discover/path.go

@@ -1,56 +0,0 @@
-package discover
-
-import (
-	"os"
-	"path/filepath"
-	"runtime"
-)
-
-// LibPath is a path to lookup dynamic libraries
-// in development it's usually 'build/lib/ollama'
-// in distribution builds it's 'lib/ollama' on Windows
-// '../lib/ollama' on Linux and the executable's directory on macOS
-// note: distribution builds, additional GPU-specific libraries are
-// found in subdirectories of the returned path, such as
-// 'cuda_v11', 'cuda_v12', 'rocm', etc.
-var LibOllamaPath string = func() string {
-	exe, err := os.Executable()
-	if err != nil {
-		return ""
-	}
-
-	if eval, err := filepath.EvalSymlinks(exe); err == nil {
-		exe = eval
-	}
-
-	var libPath string
-	switch runtime.GOOS {
-	case "windows":
-		libPath = filepath.Join(filepath.Dir(exe), "lib", "ollama")
-	case "linux":
-		libPath = filepath.Join(filepath.Dir(exe), "..", "lib", "ollama")
-	case "darwin":
-		libPath = filepath.Dir(exe)
-	}
-
-	cwd, err := os.Getwd()
-	if err != nil {
-		return ""
-	}
-
-	paths := []string{
-		libPath,
-
-		// build paths for development
-		filepath.Join(filepath.Dir(exe), "build", "lib", "ollama"),
-		filepath.Join(cwd, "build", "lib", "ollama"),
-	}
-
-	for _, p := range paths {
-		if _, err := os.Stat(p); err == nil {
-			return p
-		}
-	}
-
-	return filepath.Dir(exe)
-}()

docs/README.md

@@ -2,7 +2,7 @@
 
 ### Getting Started
 * [Quickstart](../README.md#quickstart)
-* [Examples](./examples.md)
+* [Examples](../examples)
 * [Importing models](./import.md)
 * [Linux Documentation](./linux.md)
 * [Windows Documentation](./windows.md)

docs/benchmark.md

@@ -1,59 +0,0 @@
-# Benchmark
-
-Go benchmark tests that measure end-to-end performance of a running Ollama server. Run these tests to evaluate model inference performance on your hardware and measure the impact of code changes.
-
-## When to use
-
-Run these benchmarks when:
-- Making changes to the model inference engine
-- Modifying model loading/unloading logic
-- Changing prompt processing or token generation code
-- Implementing a new model architecture
-- Testing performance across different hardware setups
-
-## Prerequisites
-- Ollama server running locally with `ollama serve` on `127.0.0.1:11434`
-## Usage and Examples
-
->[!NOTE]
->All commands must be run from the root directory of the Ollama project.
-
-Basic syntax:
-```bash
-go test -bench=. ./benchmark/... -m $MODEL_NAME
-```
-
-Required flags:
-- `-bench=.`: Run all benchmarks
-- `-m`: Model name to benchmark
-
-Optional flags:
-- `-count N`: Number of times to run the benchmark (useful for statistical analysis)
-- `-timeout T`: Maximum time for the benchmark to run (e.g. "10m" for 10 minutes)
-
-Common usage patterns:
-
-Single benchmark run with a model specified:
-```bash
-go test -bench=. ./benchmark/... -m llama3.3
-```
-
-## Output metrics
-
-The benchmark reports several key metrics:
-
-- `gen_tok/s`: Generated tokens per second
-- `prompt_tok/s`: Prompt processing tokens per second
-- `ttft_ms`: Time to first token in milliseconds
-- `load_ms`: Model load time in milliseconds
-- `gen_tokens`: Total tokens generated
-- `prompt_tokens`: Total prompt tokens processed
-
-Each benchmark runs two scenarios:
-- Cold start: Model is loaded from disk for each test
-- Warm start: Model is pre-loaded in memory
-
-Three prompt lengths are tested for each scenario:
-- Short prompt (100 tokens)
-- Medium prompt (500 tokens)
-- Long prompt (1000 tokens)

docs/development.md

@@ -1,159 +1,150 @@
 # Development
 
-Install prerequisites:
+Install required tools:
 
-- [Go](https://go.dev/doc/install)
-- C/C++ Compiler e.g. Clang on macOS, [TDM-GCC](https://github.com/jmeubank/tdm-gcc/releases/latest) (Windows amd64) or [llvm-mingw](https://github.com/mstorsjo/llvm-mingw) (Windows arm64), GCC/Clang on Linux.
+- cmake version 3.24 or higher
+- go version 1.22 or higher
+- gcc version 11.4.0 or higher
 
-Then build and run Ollama from the root directory of the repository:
+### MacOS
 
-```shell
-go run . serve
+```bash
+brew install go cmake gcc
 ```
 
-## macOS (Apple Silicon)
+Optionally enable debugging and more verbose logging:
 
-macOS Apple Silicon supports Metal which is built-in to the Ollama binary. No additional steps are required.
+```bash
+# At build time
+export CGO_CFLAGS="-g"
 
-## macOS (Intel)
-
-Install prerequisites:
-
-- [CMake](https://cmake.org/download/) or `brew install cmake`
-
-Then, configure and build the project:
-
-```shell
-cmake -B build
-cmake --build build
+# At runtime
+export OLLAMA_DEBUG=1
 ```
 
-Lastly, run Ollama:
+Get the required libraries and build the native LLM code:
 
-```shell
-go run . serve
+```bash
+go generate ./...
 ```
 
-## Windows
+Then build ollama:
 
-Install prerequisites:
-
-- [CMake](https://cmake.org/download/)
-- [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) including the Native Desktop Workload
-- (Optional) AMD GPU support
-    - [ROCm](https://rocm.docs.amd.com/en/latest/)
-    - [Ninja](https://github.com/ninja-build/ninja/releases)
-- (Optional) NVIDIA GPU support
-    - [CUDA SDK](https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64&target_version=11&target_type=exe_network)
-
-Then, configure and build the project:
-
-```shell
-cmake -B build
-cmake --build build --config Release
+```bash
+go build .
 ```
 
-> [!IMPORTANT]
-> Building for ROCm requires additional flags:
-> ```
-> cmake -B build -G Ninja -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++
-> cmake --build build --config Release
-> ```
+Now you can run `ollama`:
 
-
-Lastly, run Ollama:
-
-```shell
-go run . serve
+```bash
+./ollama
 ```
 
-## Windows (ARM)
+### Linux
 
-Windows ARM does not support additional acceleration libraries at this time.  Do not use cmake, simply `go run` or `go build`.
+#### Linux CUDA (NVIDIA)
 
-## Linux
+_Your operating system distribution may already have packages for NVIDIA CUDA. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
 
-Install prerequisites:
+Install `cmake` and `golang` as well as [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads)
+development and runtime packages.
 
-- [CMake](https://cmake.org/download/) or `sudo apt install cmake` or `sudo dnf install cmake`
-- (Optional) AMD GPU support
-    - [ROCm](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/quick-start.html)
-- (Optional) NVIDIA GPU support
-    - [CUDA SDK](https://developer.nvidia.com/cuda-downloads)
+Typically the build scripts will auto-detect CUDA, however, if your Linux distro
+or installation approach uses unusual paths, you can specify the location by
+specifying an environment variable `CUDA_LIB_DIR` to the location of the shared
+libraries, and `CUDACXX` to the location of the nvcc compiler. You can customize
+a set of target CUDA architectures by setting `CMAKE_CUDA_ARCHITECTURES` (e.g. "50;60;70")
 
-> [!IMPORTANT]
-> Ensure prerequisites are in `PATH` before running CMake.
+Then generate dependencies:
 
-
-Then, configure and build the project:
-
-```shell
-cmake -B build
-cmake --build build
+```
+go generate ./...
 ```
 
-Lastly, run Ollama:
+Then build the binary:
 
-```shell
-go run . serve
+```
+go build .
 ```
 
-## Docker
+#### Linux ROCm (AMD)
 
-```shell
-docker build .
+_Your operating system distribution may already have packages for AMD ROCm and CLBlast. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
+
+Install [CLBlast](https://github.com/CNugteren/CLBlast/blob/master/doc/installation.md) and [ROCm](https://rocm.docs.amd.com/en/latest/) development packages first, as well as `cmake` and `golang`.
+
+Typically the build scripts will auto-detect ROCm, however, if your Linux distro
+or installation approach uses unusual paths, you can specify the location by
+specifying an environment variable `ROCM_PATH` to the location of the ROCm
+install (typically `/opt/rocm`), and `CLBlast_DIR` to the location of the
+CLBlast install (typically `/usr/lib/cmake/CLBlast`). You can also customize
+the AMD GPU targets by setting AMDGPU_TARGETS (e.g. `AMDGPU_TARGETS="gfx1101;gfx1102"`)
+
+```
+go generate ./...
 ```
 
-### ROCm
+Then build the binary:
 
-```shell
-docker build --build-arg FLAVOR=rocm .
+```
+go build .
 ```
 
-## Running tests
+ROCm requires elevated privileges to access the GPU at runtime. On most distros you can add your user account to the `render` group, or run as root.
 
-To run tests, use `go test`:
+#### Advanced CPU Settings
 
-```shell
-go test ./...
+By default, running `go generate ./...` will compile a few different variations
+of the LLM library based on common CPU families and vector math capabilities,
+including a lowest-common-denominator which should run on almost any 64 bit CPU
+somewhat slowly. At runtime, Ollama will auto-detect the optimal variation to
+load. If you would like to build a CPU-based build customized for your
+processor, you can set `OLLAMA_CUSTOM_CPU_DEFS` to the llama.cpp flags you would
+like to use. For example, to compile an optimized binary for an Intel i9-9880H,
+you might use:
+
+```
+OLLAMA_CUSTOM_CPU_DEFS="-DGGML_AVX=on -DGGML_AVX2=on -DGGML_F16C=on -DGGML_FMA=on" go generate ./...
+go build .
 ```
 
-> NOTE: In rare cirumstances, you may nedd to change a package using the new
-> "synctest" package in go1.24.
->
-> If you do not have the "synctest" package enabled, you will not see build or
-> test failures resulting from your change(s), if any, locally, but CI will
-> break.
->
-> If you see failures in CI, you can either keep pushing changes to see if the
-> CI build passes, or you can enable the "synctest" package locally to see the
-> failures before pushing.
->
-> To enable the "synctest" package for testing, run the following command:
->
-> ```shell
-> GOEXPERIMENT=synctest go test ./...
-> ```
->
-> If you wish to enable synctest for all go commands, you can set the
-> `GOEXPERIMENT` environment variable in your shell profile or by using:
->
-> ```shell
-> go env -w GOEXPERIMENT=synctest
-> ```
->
-> Which will enable the "synctest" package for all go commands without needing
-> to set it for all shell sessions.
->
-> The synctest package is not required for production builds.
+#### Containerized Linux Build
 
-## Library detection
+If you have Docker available, you can build linux binaries with `./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included. The resulting binary is placed in `./dist`
 
-Ollama looks for acceleration libraries in the following paths relative to the `ollama` executable:
+### Windows
 
-* `./lib/ollama` (Windows)
-* `../lib/ollama` (Linux)
-* `.` (macOS)
-* `build/lib/ollama` (for development)
+Note: The Windows build for Ollama is still under development.
 
-If the libraries are not found, Ollama will not run with any acceleration libraries.
+First, install required tools:
+
+- MSVC toolchain - C/C++ and cmake as minimal requirements
+- Go version 1.22 or higher
+- MinGW (pick one variant) with GCC.
+  - [MinGW-w64](https://www.mingw-w64.org/)
+  - [MSYS2](https://www.msys2.org/)
+- The `ThreadJob` Powershell module: `Install-Module -Name ThreadJob -Scope CurrentUser`
+
+Then, build the `ollama` binary:
+
+```powershell
+$env:CGO_ENABLED="1"
+go generate ./...
+go build .
+```
+
+#### Windows CUDA (NVIDIA)
+
+In addition to the common Windows development tools described above, install CUDA after installing MSVC.
+
+- [NVIDIA CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html)
+
+
+#### Windows ROCm (AMD Radeon)
+
+In addition to the common Windows development tools described above, install AMDs HIP package after installing MSVC.
+
+- [AMD HIP](https://www.amd.com/en/developer/resources/rocm-hub/hip-sdk.html)
+- [Strawberry Perl](https://strawberryperl.com/)
+
+Lastly, add `ninja.exe` included with MSVC to the system path (e.g. `C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\Common7\IDE\CommonExtensions\Microsoft\CMake\Ninja`).

docs/docker.md

@@ -1,78 +1,71 @@
-# Ollama Docker image
-
-### CPU only
-
-```shell
-docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
-```
-
-### Nvidia GPU
-Install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installation).
-
-#### Install with Apt
-1.  Configure the repository
-
-    ```shell
-    curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
-        | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
-    curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
-        | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
-        | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
-    sudo apt-get update
-    ```
-
-2.  Install the NVIDIA Container Toolkit packages
-
-    ```shell
-    sudo apt-get install -y nvidia-container-toolkit
-    ```
-
-#### Install with Yum or Dnf
-1.  Configure the repository
-
-    ```shell
-    curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo \
-        | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
-    ```
-
-2. Install the NVIDIA Container Toolkit packages
-
-    ```shell
-    sudo yum install -y nvidia-container-toolkit
-    ```
-
-#### Configure Docker to use Nvidia driver
-
-```shell
-sudo nvidia-ctk runtime configure --runtime=docker
-sudo systemctl restart docker
-```
-
-#### Start the container
-
-```shell
-docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
-```
-
-> [!NOTE]  
-> If you're running on an NVIDIA JetPack system, Ollama can't automatically discover the correct JetPack version. Pass the environment variable JETSON_JETPACK=5 or JETSON_JETPACK=6 to the container to select version 5 or 6.
-
-### AMD GPU
-
-To run Ollama using Docker with AMD GPUs, use the `rocm` tag and the following command:
-
-```shell
-docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm
-```
-
-### Run model locally
-
-Now you can run a model:
-
-```shell
-docker exec -it ollama ollama run llama3.2
-```
-
-### Try different models
-
-More models can be found on the [Ollama library](https://ollama.com/library).
+# Ollama Docker image
+
+### CPU only
+
+```bash
+docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
+```
+
+### Nvidia GPU
+Install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installation).
+
+#### Install with Apt
+1.  Configure the repository
+```bash
+curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
+    | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
+curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
+    | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
+    | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
+sudo apt-get update
+```
+2.  Install the NVIDIA Container Toolkit packages
+```bash
+sudo apt-get install -y nvidia-container-toolkit
+```
+
+#### Install with Yum or Dnf
+1.  Configure the repository
+    
+```bash
+curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo \
+    | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
+```
+    
+2. Install the NVIDIA Container Toolkit packages
+    
+```bash
+sudo yum install -y nvidia-container-toolkit
+```
+
+#### Configure Docker to use Nvidia driver 
+```
+sudo nvidia-ctk runtime configure --runtime=docker
+sudo systemctl restart docker
+```
+
+#### Start the container
+
+```bash
+docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
+```
+
+### AMD GPU
+
+To run Ollama using Docker with AMD GPUs, use the `rocm` tag and the following command:
+
+```
+docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm
+```
+
+### Run model locally
+
+Now you can run a model:
+
+```
+docker exec -it ollama ollama run llama3
+```
+
+### Try different models
+
+More models can be found on the [Ollama library](https://ollama.com/library).

docs/examples.md

@@ -1,20 +0,0 @@
-# Examples
-
-This directory contains different examples of using Ollama.
-
-## Python examples
-Ollama Python examples at [ollama-python/examples](https://github.com/ollama/ollama-python/tree/main/examples)
-
-
-## JavaScript examples
-Ollama JavaScript examples at [ollama-js/examples](https://github.com/ollama/ollama-js/tree/main/examples)
-
-
-## OpenAI compatibility examples
-Ollama OpenAI compatibility examples at [ollama/examples/openai](../docs/openai.md)
-
-
-## Community examples
-
-- [LangChain Ollama Python](https://python.langchain.com/docs/integrations/chat/ollama/)
-- [LangChain Ollama JS](https://js.langchain.com/docs/integrations/chat/ollama/)

docs/faq.md

@@ -20,17 +20,11 @@ Please refer to the [GPU docs](./gpu.md).
 
 ## How can I specify the context window size?
 
-By default, Ollama uses a context window size of 2048 tokens. 
-
-This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use: 
-
-```shell
-OLLAMA_CONTEXT_LENGTH=8192 ollama serve
-```
+By default, Ollama uses a context window size of 2048 tokens.
 
 To change this when using `ollama run`, use `/set parameter`:
 
-```shell
+```
 /set parameter num_ctx 4096
 ```
 
@@ -38,7 +32,7 @@ When using the API, specify the `num_ctx` parameter:
 
 ```shell
 curl http://localhost:11434/api/generate -d '{
-  "model": "llama3.2",
+  "model": "llama3",
   "prompt": "Why is the sky blue?",
   "options": {
     "num_ctx": 4096
@@ -52,15 +46,10 @@ Use the `ollama ps` command to see what models are currently loaded into memory.
 
 ```shell
 ollama ps
+NAME      	ID          	SIZE 	PROCESSOR	UNTIL
+llama3:70b	bcfb190ca3a7	42 GB	100% GPU 	4 minutes from now
 ```
 
-> **Output**:
->
-> ```
-> NAME      	ID          	SIZE 	PROCESSOR	UNTIL
-> llama3:70b	bcfb190ca3a7	42 GB	100% GPU 	4 minutes from now
-> ```
-
 The `Processor` column will show which memory the model was loaded in to:
 * `100% GPU` means the model was loaded entirely into the GPU
 * `100% CPU` means the model was loaded entirely in system memory
@@ -77,7 +66,7 @@ If Ollama is run as a macOS application, environment variables should be set usi
 1. For each environment variable, call `launchctl setenv`.
 
     ```bash
-    launchctl setenv OLLAMA_HOST "0.0.0.0:11434"
+    launchctl setenv OLLAMA_HOST "0.0.0.0"
     ```
 
 2. Restart Ollama application.
@@ -92,14 +81,14 @@ If Ollama is run as a systemd service, environment variables should be set using
 
     ```ini
     [Service]
-    Environment="OLLAMA_HOST=0.0.0.0:11434"
+    Environment="OLLAMA_HOST=0.0.0.0"
     ```
 
 3. Save and exit.
 
 4. Reload `systemd` and restart Ollama:
 
-   ```shell
+   ```bash
    systemctl daemon-reload
    systemctl restart ollama
    ```
@@ -122,10 +111,7 @@ On Windows, Ollama inherits your user and system environment variables.
 
 ## How do I use Ollama behind a proxy?
 
-Ollama pulls models from the Internet and may require a proxy server to access the models. Use `HTTPS_PROXY` to redirect outbound requests through the proxy. Ensure the proxy certificate is installed as a system certificate. Refer to the section above for how to use environment variables on your platform.
-
-> [!NOTE]
-> Avoid setting `HTTP_PROXY`. Ollama does not use HTTP for model pulls, only HTTPS. Setting `HTTP_PROXY` may interrupt client connections to the server.
+Ollama is compatible with proxy servers if `HTTP_PROXY` or `HTTPS_PROXY` are configured. When using either variables, ensure it is set where `ollama serve` can access the values. When using `HTTPS_PROXY`, ensure the proxy certificate is installed as a system certificate. Refer to the section above for how to use environment variables on your platform.
 
 ### How do I use Ollama behind a proxy in Docker?
 
@@ -162,7 +148,7 @@ Refer to the section [above](#how-do-i-configure-ollama-server) for how to set e
 
 Ollama runs an HTTP server and can be exposed using a proxy server such as Nginx. To do so, configure the proxy to forward requests and optionally set required headers (if not exposing Ollama on the network). For example, with Nginx:
 
-```nginx
+```
 server {
     listen 80;
     server_name example.com;  # Replace with your domain or IP
@@ -193,13 +179,6 @@ cloudflared tunnel --url http://localhost:11434 --http-host-header="localhost:11
 
 Ollama allows cross-origin requests from `127.0.0.1` and `0.0.0.0` by default. Additional origins can be configured with `OLLAMA_ORIGINS`.
 
-For browser extensions, you'll need to explicitly allow the extension's origin pattern. Set `OLLAMA_ORIGINS` to include `chrome-extension://*`, `moz-extension://*`, and `safari-web-extension://*` if you wish to allow all browser extensions access, or specific extensions as needed:
-
-```
-# Allow all Chrome, Firefox, and Safari extensions
-OLLAMA_ORIGINS=chrome-extension://*,moz-extension://*,safari-web-extension://* ollama serve
-```
-
 Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
 
 ## Where are models stored?
@@ -212,8 +191,6 @@ Refer to the section [above](#how-do-i-configure-ollama-server) for how to set e
 
 If a different directory needs to be used, set the environment variable `OLLAMA_MODELS` to the chosen directory.
 
-> Note: on Linux using the standard installer, the `ollama` user needs read and write access to the specified directory. To assign the directory to the `ollama` user run `sudo chown -R ollama:ollama <directory>`.
-
 Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
 
 ## How can I use Ollama in Visual Studio Code?
@@ -239,52 +216,43 @@ properties.
 If you are using the API you can preload a model by sending the Ollama server an empty request. This works with both the `/api/generate` and `/api/chat` API endpoints.
 
 To preload the mistral model using the generate endpoint, use:
-
 ```shell
 curl http://localhost:11434/api/generate -d '{"model": "mistral"}'
 ```
 
 To use the chat completions endpoint, use:
-
 ```shell
 curl http://localhost:11434/api/chat -d '{"model": "mistral"}'
 ```
 
 To preload a model using the CLI, use the command:
-
 ```shell
-ollama run llama3.2 ""
+ollama run llama3 ""
 ```
 
 ## How do I keep a model loaded in memory or make it unload immediately?
 
-By default models are kept in memory for 5 minutes before being unloaded. This allows for quicker response times if you're making numerous requests to the LLM. If you want to immediately unload a model from memory, use the `ollama stop` command:
+By default models are kept in memory for 5 minutes before being unloaded. This allows for quicker response times if you are making numerous requests to the LLM. You may, however, want to free up the memory before the 5 minutes have elapsed or keep the model loaded indefinitely. Use the `keep_alive` parameter with either the `/api/generate` and `/api/chat` API endpoints to control how long the model is left in memory.
 
-```shell
-ollama stop llama3.2
-```
-
-If you're using the API, use the `keep_alive` parameter with the `/api/generate` and `/api/chat` endpoints to set the amount of time that a model stays in memory. The `keep_alive` parameter can be set to:
+The `keep_alive` parameter can be set to:
 * a duration string (such as "10m" or "24h")
 * a number in seconds (such as 3600)
 * any negative number which will keep the model loaded in memory (e.g. -1 or "-1m")
 * '0' which will unload the model immediately after generating a response
 
 For example, to preload a model and leave it in memory use:
-
 ```shell
-curl http://localhost:11434/api/generate -d '{"model": "llama3.2", "keep_alive": -1}'
+curl http://localhost:11434/api/generate -d '{"model": "llama3", "keep_alive": -1}'
 ```
 
 To unload the model and free up memory use:
-
 ```shell
-curl http://localhost:11434/api/generate -d '{"model": "llama3.2", "keep_alive": 0}'
+curl http://localhost:11434/api/generate -d '{"model": "llama3", "keep_alive": 0}'
 ```
 
-Alternatively, you can change the amount of time all models are loaded into memory by setting the `OLLAMA_KEEP_ALIVE` environment variable when starting the Ollama server. The `OLLAMA_KEEP_ALIVE` variable uses the same parameter types as the `keep_alive` parameter types mentioned above. Refer to the section explaining [how to configure the Ollama server](#how-do-i-configure-ollama-server) to correctly set the environment variable.
+Alternatively, you can change the amount of time all models are loaded into memory by setting the `OLLAMA_KEEP_ALIVE` environment variable when starting the Ollama server. The `OLLAMA_KEEP_ALIVE` variable uses the same parameter types as the `keep_alive` parameter types mentioned above. Refer to section explaining [how to configure the Ollama server](#how-do-i-configure-ollama-server) to correctly set the environment variable.
 
-The `keep_alive` API parameter with the `/api/generate` and `/api/chat` API endpoints will override the `OLLAMA_KEEP_ALIVE` setting.
+If you wish to override the `OLLAMA_KEEP_ALIVE` setting, use the `keep_alive` API parameter with the `/api/generate` or `/api/chat` API endpoints.
 
 ## How do I manage the maximum number of requests the Ollama server can queue?
 
@@ -304,32 +272,4 @@ The following server settings may be used to adjust how Ollama handles concurren
 - `OLLAMA_NUM_PARALLEL` - The maximum number of parallel requests each model will process at the same time.  The default will auto-select either 4 or 1 based on available memory.
 - `OLLAMA_MAX_QUEUE` - The maximum number of requests Ollama will queue when busy before rejecting additional requests. The default is 512
 
-Note: Windows with Radeon GPUs currently default to 1 model maximum due to limitations in ROCm v5.7 for available VRAM reporting.  Once ROCm v6.2 is available, Windows Radeon will follow the defaults above.  You may enable concurrent model loads on Radeon on Windows, but ensure you don't load more models than will fit into your GPUs VRAM.
-
-## How does Ollama load models on multiple GPUs?
-
-When loading a new model, Ollama evaluates the required VRAM for the model against what is currently available.  If the model will entirely fit on any single GPU, Ollama will load the model on that GPU.  This typically provides the best performance as it reduces the amount of data transferring across the PCI bus during inference.  If the model does not fit entirely on one GPU, then it will be spread across all the available GPUs.
-
-## How can I enable Flash Attention?
-
-Flash Attention is a feature of most modern models that can significantly reduce memory usage as the context size grows.  To enable Flash Attention, set the `OLLAMA_FLASH_ATTENTION` environment variable to `1` when starting the Ollama server.
-
-## How can I set the quantization type for the K/V cache?
-
-The K/V context cache can be quantized to significantly reduce memory usage when Flash Attention is enabled.
-
-To use quantized K/V cache with Ollama you can set the following environment variable:
-
-- `OLLAMA_KV_CACHE_TYPE` - The quantization type for the K/V cache.  Default is `f16`.
-
-> Note: Currently this is a global option - meaning all models will run with the specified quantization type.
-
-The currently available K/V cache quantization types are:
-
-- `f16` - high precision and memory usage (default).
-- `q8_0` - 8-bit quantization, uses approximately 1/2 the memory of `f16` with a very small loss in precision, this usually has no noticeable impact on the model's quality (recommended if not using f16).
-- `q4_0` - 4-bit quantization, uses approximately 1/4 the memory of `f16` with a small-medium loss in precision that may be more noticeable at higher context sizes.
-
-How much the cache quantization impacts the model's response quality will depend on the model and the task.  Models that have a high GQA count (e.g. Qwen2) may see a larger impact on precision from quantization than models with a low GQA count.
-
-You may need to experiment with different quantization types to find the best balance between memory usage and quality.
+Note: Windows with Radeon GPUs currently default to 1 model maximum due to limitations in ROCm v5.7 for available VRAM reporting.  Once ROCm v6 is available, Windows Radeon will follow the defaults above.  You may enable concurrent model loads on Radeon on Windows, but ensure you don't load more models than will fit into your GPUs VRAM.