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3 Commits

Author SHA1 Message Date
Josh Yan
5dc5a295bf added testcase 2024-06-03 17:28:05 -07:00
Josh Yan
e21e6b2a33 added testcase 2024-06-03 17:27:38 -07:00
Josh Yan
a240ea3367 humanNumbers formats to 3 digits, added trillion case for future 2024-06-03 17:26:02 -07:00
665 changed files with 22374 additions and 173856 deletions

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

12
.gitattributes vendored
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@ -1,11 +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
* text=auto
*.go text eol=lf
llm/ext_server/* linguist-vendored

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@ -1,9 +1,5 @@
name: release
env:
ROCM_WINDOWS_URL: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe
MSYS2_URL: https://github.com/msys2/msys2-installer/releases/download/2024-07-27/msys2-x86_64-20240727.exe
on:
push:
tags:
@ -12,7 +8,7 @@ on:
jobs:
# Full build of the Mac assets
build-darwin:
runs-on: macos-13
runs-on: macos-12
environment: release
steps:
- uses: actions/checkout@v4
@ -43,8 +39,8 @@ jobs:
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
@ -52,8 +48,8 @@ jobs:
with:
name: dist-darwin
path: |
dist/Ollama-darwin.zip
dist/ollama-darwin
dist/*arwin*
!dist/*-cov
# Windows builds take a long time to both install the dependencies and build, so parallelize
# CPU generation step
@ -64,286 +60,14 @@ jobs:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
- uses: actions/checkout@v4
- name: Set make jobs default
run: |
echo "MAKEFLAGS=--jobs=$((Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- name: Add msys paths
run: |
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 msys2 tools
run: |
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
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- 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'
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make
name: make
- uses: actions/upload-artifact@v4
with:
name: generate-windows-cpu
path: |
build/**/*
dist/windows-amd64/**
# ROCm generation step
generate-windows-rocm:
environment: release
runs-on: windows
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
- uses: actions/checkout@v4
- name: Set make jobs default
run: |
echo "MAKEFLAGS=--jobs=$((Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- name: Add msys paths
run: |
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 msys2 tools
run: |
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
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
# ROCM installation steps
- name: 'Cache ROCm installer'
id: cache-rocm
uses: actions/cache@v4
with:
path: rocm-install.exe
key: ${{ env.ROCM_WINDOWS_URL }}
- name: 'Conditionally Download ROCm'
if: steps.cache-rocm.outputs.cache-hit != 'true'
run: |
$ErrorActionPreference = "Stop"
Invoke-WebRequest -Uri "${env:ROCM_WINDOWS_URL}" -OutFile "rocm-install.exe"
- name: 'Install ROCm'
run: |
Start-Process "rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
- name: 'Verify ROCm'
run: |
& 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
echo "HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path | select -first 1)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: make rocm runner
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'
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make -C llama print-HIP_PATH print-HIP_LIB_DIR
make rocm
- uses: actions/upload-artifact@v4
with:
name: generate-windows-rocm
path: |
build/**/*
dist/windows-amd64/**
# CUDA generation step
generate-windows-cuda:
environment: release
runs-on: windows
strategy:
matrix:
cuda:
- version: "11.3"
url: https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.89_win10.exe
- version: "12.4"
url: https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda_12.4.0_551.61_windows.exe
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
- uses: actions/checkout@v4
- name: Set make jobs default
run: |
echo "MAKEFLAGS=--jobs=$((Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: Set Version
shell: bash
run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
- name: Install msys2
run: |
$msys2_url="https://github.com/msys2/msys2-installer/releases/download/2024-07-27/msys2-x86_64-20240727.exe"
write-host "Downloading msys2"
Invoke-WebRequest -Uri "${msys2_url}" -OutFile "${env:RUNNER_TEMP}\msys2.exe"
write-host "Installing msys2"
Start-Process "${env:RUNNER_TEMP}\msys2.exe" -ArgumentList @("in", "--confirm-command", "--accept-messages", "--root", "C:/msys64") -NoNewWindow -Wait
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang", "make") -NoNewWindow -Wait
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: verify tools
run: |
get-command gcc
gcc --version
get-command make
make --version
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
# CUDA installation steps
- name: 'Cache CUDA installer'
id: cache-cuda
uses: actions/cache@v4
with:
path: cuda-install.exe
key: ${{ matrix.cuda.url }}
- name: 'Conditionally Download CUDA'
if: steps.cache-cuda.outputs.cache-hit != 'true'
run: |
$ErrorActionPreference = "Stop"
Invoke-WebRequest -Uri "${{ matrix.cuda.url }}" -OutFile "cuda-install.exe"
- name: 'Install CUDA'
run: |
$subpackages = @("cudart", "nvcc", "cublas", "cublas_dev") | foreach-object {"${_}_${{ matrix.cuda.version }}"}
Start-Process "cuda-install.exe" -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
- name: 'Verify CUDA'
run: |
& (resolve-path "c:\Program Files\NVIDIA*\CUDA\v*\bin\nvcc.exe")[0] --version
$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" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=$cudaPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
echo "CUDA_PATH_V${cudaVer}=$cudaPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
echo "CUDA_PATH_VX_Y=CUDA_PATH_V${cudaVer}" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: make cuda runner
run: |
import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make cuda_v$(($env:CUDA_PATH | split-path -leaf) -replace 'v(\d+).*', '$1')
- uses: actions/upload-artifact@v4
with:
name: generate-windows-cuda-${{ matrix.cuda.version }}
path: |
build/**/*
dist/windows-amd64/**
# windows arm64 generate, go build, and zip file (no installer)
# Output of this build is aggregated into the final x86 build
# for a unified windows installer
windows-arm64:
runs-on: windows-arm64
environment: release
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
# The current Windows arm64 beta image has effectively zero dev tools installed...
- name: Install git and gzip
run: |
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'))
choco install -y --no-progress git gzip
echo "C:\Program Files\Git\cmd" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\ProgramData\chocolatey\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
# pacman is buggy on win arm64, so we avoid using it, but rely on the binary artifacts
# we download the sfx (7zip bundle) which isn't fully set up, but the binaries we need to build work
- name: Install msys2 x64
run: |
$url="https://github.com/msys2/msys2-installer/releases/download/2024-07-27/msys2-base-x86_64-20240727.sfx.exe"
write-host "Downloading MSYS2"
Invoke-WebRequest -Uri "$url" -outfile "${env:RUNNER_TEMP}\msys2.exe"
write-host "Installing msys2"
Start-Process "${env:RUNNER_TEMP}\msys2.exe" -ArgumentList @(
'-y', '-oC:\'
) -NoNewWindow -Wait
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
# since pacman isn't reliable, we just download the tar file and extract directly
- name: Downloading and extracting msys2 make tar file
run: |
$url="https://mirror.msys2.org/msys/x86_64/make-4.4.1-2-x86_64.pkg.tar.zst"
write-host "Downloading make"
Invoke-WebRequest -Uri "$url" -outfile c:\msys64\make.tar.zst
cd c:\msys64; tar -xf make.tar.zst
rm c:\msys64\make.tar.zst
- name: Verify Make works properly
run: |
echo $env:PATH
make --version
- name: Install Visual Studio 2022
run: |
$components = @(
"Microsoft.VisualStudio.Component.CoreEditor",
"Microsoft.VisualStudio.Workload.CoreEditor",
"Microsoft.VisualStudio.Component.Roslyn.Compiler",
"Microsoft.Component.MSBuild",
"Microsoft.VisualStudio.Component.TextTemplating",
"Microsoft.VisualStudio.Component.Debugger.JustInTime",
"Microsoft.VisualStudio.Component.VC.CoreIde",
"Microsoft.VisualStudio.Component.VC.Tools.x86.x64",
"Microsoft.VisualStudio.Component.Windows11SDK.22621",
"Microsoft.VisualStudio.Component.VC.Tools.ARM64EC",
"Microsoft.VisualStudio.Component.VC.Tools.ARM64",
"Microsoft.VisualStudio.Component.VC.ATL",
"Microsoft.VisualStudio.Component.VC.ATL.ARM64",
"Microsoft.VisualStudio.Component.Graphics",
"Microsoft.VisualStudio.Component.VC.Redist.14.Latest",
"Microsoft.VisualStudio.ComponentGroup.NativeDesktop.Core",
"Microsoft.VisualStudio.Component.Windows11Sdk.WindowsPerformanceToolkit",
"Microsoft.VisualStudio.Component.CppBuildInsights",
"Microsoft.VisualStudio.Component.VC.DiagnosticTools",
"Microsoft.VisualStudio.ComponentGroup.WebToolsExtensions.CMake",
"Microsoft.VisualStudio.Component.VC.CMake.Project",
"Microsoft.VisualStudio.Component.VC.ASAN",
"Microsoft.VisualStudio.Component.Vcpkg",
"Microsoft.VisualStudio.Workload.NativeDesktop"
)
$config = @{
"version" = "1.0"
"components" = $components
"extensions" = @()
}
$configPath = "${env:RUNNER_TEMP}\vsconfig"
$config | ConvertTo-Json | Out-File -FilePath $configPath
$bootstrapperFilePath = "${env:RUNNER_TEMP}\vs_community.exe"
write-host "Downloading Visual Studio 2022"
Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vs_community.exe" -outfile $bootstrapperFilePath
$bootstrapperArgumentList = ('/c', $bootstrapperFilePath, '--config', $configPath, '--quiet', '--wait' )
write-host "Installing Visual Studio 2022"
$process = Start-Process -FilePath cmd.exe -ArgumentList $bootstrapperArgumentList -Wait -PassThru
$exitCode = $process.ExitCode
write-host $exitCode
# pacman in mingw/msys2 is ~broken on windows arm right now - hangs consistently during attempts to install
# so we'll use this alternative GCC binary
- name: Install llvm-mingw GCC
run: |
$gcc_url="https://github.com/mstorsjo/llvm-mingw/releases/download/20240619/llvm-mingw-20240619-ucrt-aarch64.zip"
write-host "Downloading llvm-mingw"
Invoke-WebRequest -Uri "${gcc_url}" -OutFile "${env:RUNNER_TEMP}\gcc.zip"
write-host "Unpacking llvm-mingw"
expand-archive -path "${env:RUNNER_TEMP}\gcc.zip" -destinationpath "c:\"
mv c:\llvm-mingw-* c:\llvm-mingw
echo "c:\llvm-mingw\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Verify GCC
run: |
echo $env:PATH
gcc --version
- uses: actions/checkout@v4
- name: Set Version
run: |
$ver=${env:GITHUB_REF_NAME}.trim("v")
echo VERSION=$ver | Out-File -FilePath ${env:GITHUB_ENV} -Encoding utf8 -Append
- uses: 'google-github-actions/auth@v2'
with:
project_id: 'ollama'
credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
- run: echo "${{ vars.OLLAMA_CERT }}" | Out-File -FilePath ollama_inc.crt -Encoding utf8
- run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
- name: install Windows SDK 8.1 to get signtool
run: |
$ErrorActionPreference = "Stop"
@ -368,23 +92,180 @@ jobs:
- run: go get ./...
- run: |
$gopath=(get-command go).source | split-path -parent
$gccpath=(get-command gcc).source | split-path -parent
import-module 'C:\Program Files\Microsoft Visual Studio\2022\Community\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -Arch arm64 -vsinstallpath 'C:\Program Files\Microsoft Visual Studio\2022\Community' -skipautomaticlocation
$env:PATH="$gopath;$gccpath;$env:PATH"
echo $env:PATH
$env:ARCH="arm64"
.\scripts\build_windows.ps1 buildOllama buildApp gatherDependencies sign distZip
name: 'Windows Build'
& "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: windows-arm64
name: generate-windows-cpu
path: |
dist/windows-arm64/**
dist/windows-arm64-app.exe
dist/ollama-windows-arm64.zip
llm/build/**/bin/*
llm/build/**/*.a
dist/windows-amd64/**
# Import the prior generation steps plus the full arm64 build, and build the final windows assets
# ROCm generation step
generate-windows-rocm:
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 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: |
$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
@ -392,7 +273,6 @@ jobs:
- generate-windows-cuda
- generate-windows-rocm
- generate-windows-cpu
- windows-arm64
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
@ -424,24 +304,6 @@ jobs:
write-host "Installing plugin"
& "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
write-host "plugin installed"
- name: Install msys2
run: |
$msys2_url="https://github.com/msys2/msys2-installer/releases/download/2024-07-27/msys2-x86_64-20240727.exe"
write-host "Downloading msys2"
Invoke-WebRequest -Uri "${msys2_url}" -OutFile "${env:RUNNER_TEMP}\msys2.exe"
write-host "Installing msys2"
Start-Process "${env:RUNNER_TEMP}\msys2.exe" -ArgumentList @("in", "--confirm-command", "--accept-messages", "--root", "C:/msys64") -NoNewWindow -Wait
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang", "make") -NoNewWindow -Wait
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: verify tools
run: |
get-command gcc
gcc --version
get-command make
make --version
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
@ -452,24 +314,24 @@ jobs:
name: generate-windows-cpu
- uses: actions/download-artifact@v4
with:
name: generate-windows-cuda-11.3
name: generate-windows-cuda
- uses: actions/download-artifact@v4
with:
name: generate-windows-cuda-12.4
name: windows-cuda-deps
- uses: actions/download-artifact@v4
with:
name: windows-rocm-deps
- uses: actions/download-artifact@v4
with:
name: generate-windows-rocm
- uses: actions/download-artifact@v4
with:
name: windows-arm64
path: dist
- run: dir build
- run: dir llm/build
- 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'
$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"
$env:ARCH="amd64"
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
& .\scripts\build_windows.ps1
- uses: actions/upload-artifact@v4
with:
@ -483,7 +345,9 @@ jobs:
environment: release
runs-on: linux
env:
PLATFORM: linux/amd64
OLLAMA_SKIP_MANIFEST_CREATE: '1'
BUILD_ARCH: amd64
PUSH: '1'
steps:
- uses: actions/checkout@v4
with:
@ -491,8 +355,15 @@ jobs:
- name: Set Version
shell: bash
run: echo "VERSION=${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 }}
- run: |
./scripts/build_linux.sh
./scripts/build_docker.sh
mv dist/deps/* dist/
- uses: actions/upload-artifact@v4
with:
name: dist-linux-amd64
@ -506,7 +377,9 @@ jobs:
environment: release
runs-on: linux-arm64
env:
PLATFORM: linux/arm64
OLLAMA_SKIP_MANIFEST_CREATE: '1'
BUILD_ARCH: arm64
PUSH: '1'
steps:
- uses: actions/checkout@v4
with:
@ -535,8 +408,14 @@ jobs:
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
@ -544,178 +423,6 @@ jobs:
dist/*linux*
!dist/*-cov
# Container image build
build-container-image:
environment: release
strategy:
matrix:
runner:
- linux
- linux-arm64
runs-on: ${{ matrix.runner }}
env:
FINAL_IMAGE_REPO: ollama/ollama
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: 'Install Docker'
if: ${{ startsWith(matrix.runner, 'linux-arm64') }}
run: |
sudo apt-get update
sudo apt-get install -y ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc
echo "deb [arch=$(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: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.FINAL_IMAGE_REPO }}
flavor: |
latest=false
tags: |
type=ref,enable=true,priority=600,prefix=0.0.0-pr,suffix=,event=pr
type=semver,pattern={{version}}
- name: Set Version
shell: bash
run: |
machine=$(uname -m)
case ${machine} in
x86_64) echo ARCH=amd64; echo PLATFORM_PAIR=linux-amd64 ;;
aarch64) echo ARCH=arm64; echo PLATFORM_PAIR=linux-arm64 ;;
esac >>$GITHUB_ENV
echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${{ env.DOCKER_METADATA_OUTPUT_VERSION }}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_ENV
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- name: Build and push by digest
id: build
uses: docker/build-push-action@v6
with:
context: "."
platforms: linux/${{ env.ARCH }}
build-args: |
GOFLAGS
outputs: type=image,name=${{ env.FINAL_IMAGE_REPO }},push-by-digest=true,name-canonical=true,push=true
- name: Export digest
run: |
mkdir -p /tmp/digests
digest="${{ steps.build.outputs.digest }}"
touch "/tmp/digests/${digest#sha256:}"
- name: Upload digest
uses: actions/upload-artifact@v4
with:
name: digests-${{ env.PLATFORM_PAIR }}
path: /tmp/digests/*
if-no-files-found: error
retention-days: 1
merge:
environment: release
runs-on: linux
needs:
- build-container-image
env:
FINAL_IMAGE_REPO: ollama/ollama
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Download digests
uses: actions/download-artifact@v4
with:
path: /tmp/digests
pattern: digests-*
merge-multiple: true
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.FINAL_IMAGE_REPO }}
flavor: |
latest=false
tags: |
type=ref,enable=true,priority=600,prefix=0.0.0-pr,suffix=,event=pr
type=semver,pattern={{version}}
- name: Set Version
shell: bash
run: |
machine=$(uname -m)
case ${machine} in
x86_64) echo ARCH=amd64; echo PLATFORM_PAIR=linux-amd64 ;;
aarch64) echo ARCH=arm64; echo PLATFORM_PAIR=linux-arm64 ;;
esac >>$GITHUB_ENV
echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${{ env.DOCKER_METADATA_OUTPUT_VERSION }}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_ENV
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- name: Create manifest list and push
working-directory: /tmp/digests
run: |
docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
$(printf '${{ env.FINAL_IMAGE_REPO }}@sha256:%s ' *)
- name: Inspect image
run: |
docker buildx imagetools inspect ${{ env.FINAL_IMAGE_REPO }}:${{ steps.meta.outputs.version }}
build-container-image-rocm:
environment: release
runs-on: linux
env:
FINAL_IMAGE_REPO: ollama/ollama
ARCH: amd64
PLATFORM_PAIR: linux-amd64
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.FINAL_IMAGE_REPO }}
flavor: |
latest=false
tags: |
type=ref,enable=true,priority=600,prefix=0.0.0-pr,suffix=,event=pr
type=semver,pattern={{version}}
- name: Set Version
shell: bash
run: |
echo GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${{ env.DOCKER_METADATA_OUTPUT_VERSION }}\" \"-X=github.com/ollama/ollama/server.mode=release\"'" >>$GITHUB_ENV
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- name: Build and push by digest
id: build
uses: docker/build-push-action@v6
with:
context: "."
target: runtime-rocm
build-args: |
GOFLAGS
tags: ${{ env.FINAL_IMAGE_REPO }}:${{ env.DOCKER_METADATA_OUTPUT_VERSION}}-rocm
push: true
# Aggregate all the assets and ship a release
release:
needs:
@ -728,7 +435,8 @@ jobs:
permissions:
contents: write
env:
GH_TOKEN: ${{ github.token }}
OLLAMA_SKIP_IMAGE_BUILD: '1'
PUSH: '1'
steps:
- uses: actions/checkout@v4
- name: Set Version
@ -736,6 +444,12 @@ jobs:
run: |
echo "VERSION=${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:
username: ${{ vars.DOCKER_USER }}
password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
- run: ./scripts/build_docker.sh
- name: Retrieve built artifact
uses: actions/download-artifact@v4
with:
@ -744,23 +458,17 @@ jobs:
merge-multiple: true
- run: |
ls -lh dist/
(cd dist; find . -type f | xargs sha256sum > ../sha256sum.txt)
mv sha256sum.txt dist/
(cd dist; sha256sum * > sha256sum.txt)
cat dist/sha256sum.txt
- name: Create or update Release
run: |
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 ${{ 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 ${{ env.RELEASE_VERSION }} pointing to tag ${GITHUB_REF_NAME}"
gh release create ${GITHUB_REF_NAME} \
--title ${{ env.RELEASE_VERSION }} \
--draft \
--generate-notes \
--prerelease
fi
echo "Uploading artifacts for tag ${GITHUB_REF_NAME}"
gh release upload ${GITHUB_REF_NAME} dist/* --clobber
- uses: ncipollo/release-action@v1
with:
name: ${{ env.RELEASE_VERSION }}
allowUpdates: true
artifacts: 'dist/*'
draft: true
prerelease: true
omitBodyDuringUpdate: true
generateReleaseNotes: true
omitDraftDuringUpdate: true
omitPrereleaseDuringUpdate: true
replacesArtifacts: true

View File

@ -1,11 +1,5 @@
name: test
env:
ROCM_WINDOWS_URL: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe
MSYS2_URL: https://github.com/msys2/msys2-installer/releases/download/2024-07-27/msys2-x86_64-20240727.exe
CUDA_12_WINDOWS_URL: https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda_12.4.0_551.61_windows.exe
CUDA_12_WINDOWS_VER: 12.4
concurrency:
# For PRs, later CI runs preempt previous ones. e.g. a force push on a PR
# cancels running CI jobs and starts all new ones.
@ -27,7 +21,9 @@ jobs:
changes:
runs-on: ubuntu-latest
outputs:
RUNNERS: ${{ steps.changes.outputs.RUNNERS }}
GENERATE: ${{ steps.changes.outputs.GENERATE }}
GENERATE_CUDA: ${{ steps.changes.outputs.GENERATE_CUDA }}
GENERATE_ROCM: ${{ steps.changes.outputs.GENERATE_ROCM }}
steps:
- uses: actions/checkout@v4
with:
@ -42,167 +38,14 @@ jobs:
}
{
echo RUNNERS=$(changed 'llama/**')
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
runners-linux-cuda:
generate:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
strategy:
matrix:
cuda-version:
- '11.8.0'
runs-on: linux
container: nvidia/cuda:${{ matrix.cuda-version }}-devel-ubuntu20.04
steps:
- run: |
apt-get update && apt-get install -y git build-essential curl
env:
DEBIAN_FRONTEND: noninteractive
- uses: actions/checkout@v4
- uses: actions/setup-go@v4
with:
go-version-file: go.mod
cache: true
- run: go get ./...
- run: |
git config --global --add safe.directory /__w/ollama/ollama
cores=$(grep '^core id' /proc/cpuinfo |sort -u|wc -l)
make -j $cores cuda_v11
runners-linux-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
strategy:
matrix:
rocm-version:
- '6.1.2'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
- run: |
apt-get update && apt-get install -y git build-essential curl rocm-libs
env:
DEBIAN_FRONTEND: noninteractive
- uses: actions/checkout@v4
- uses: actions/setup-go@v4
with:
go-version-file: go.mod
cache: true
- run: go get ./...
- run: |
git config --global --add safe.directory /__w/ollama/ollama
cores=$(grep '^core id' /proc/cpuinfo |sort -u|wc -l)
make -j $cores rocm
# ROCm generation step
runners-windows-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
runs-on: windows
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- name: Set make jobs default
run: |
echo "MAKEFLAGS=--jobs=$((Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
# ROCM installation steps
- name: 'Cache ROCm installer'
id: cache-rocm
uses: actions/cache@v4
with:
path: rocm-install.exe
key: ${{ env.ROCM_WINDOWS_URL }}
- name: 'Conditionally Download ROCm'
if: steps.cache-rocm.outputs.cache-hit != 'true'
run: |
$ErrorActionPreference = "Stop"
Invoke-WebRequest -Uri "${env:ROCM_WINDOWS_URL}" -OutFile "rocm-install.exe"
- name: 'Install ROCm'
run: |
Start-Process "rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
- name: 'Verify ROCm'
run: |
& 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' --version
echo "HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path | select -first 1)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: Add msys paths
run: |
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 msys2 tools
run: |
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
- name: make rocm runner
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'
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make -C llama print-HIP_PATH print-HIP_LIB_DIR
make rocm
# CUDA generation step
runners-windows-cuda:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
runs-on: windows
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- name: Set make jobs default
run: |
echo "MAKEFLAGS=--jobs=$((Get-ComputerInfo -Property CsProcessors).CsProcessors.NumberOfCores)" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
# CUDA installation steps
- name: 'Cache CUDA installer'
id: cache-cuda
uses: actions/cache@v4
with:
path: cuda-install.exe
key: ${{ env.CUDA_12_WINDOWS_URL }}
- name: 'Conditionally Download CUDA'
if: steps.cache-cuda.outputs.cache-hit != 'true'
run: |
$ErrorActionPreference = "Stop"
Invoke-WebRequest -Uri "${env:CUDA_12_WINDOWS_URL}" -OutFile "cuda-install.exe"
- name: 'Install CUDA'
run: |
$subpackages = @("cudart", "nvcc", "cublas", "cublas_dev") | foreach-object {"${_}_${{ env.CUDA_12_WINDOWS_VER }}"}
Start-Process "cuda-install.exe" -ArgumentList (@("-s") + $subpackages) -NoNewWindow -Wait
- name: 'Verify CUDA'
run: |
& (resolve-path "c:\Program Files\NVIDIA*\CUDA\v*\bin\nvcc.exe")[0] --version
$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" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=$cudaPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
echo "CUDA_PATH_V${cudaVer}=$cudaPath" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
echo "CUDA_PATH_VX_Y=CUDA_PATH_V${cudaVer}" | Out-File -FilePath $env:GITHUB_ENV -Encoding utf8 -Append
- name: Add msys paths
run: |
echo "c:\msys64\usr\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\msys64\clang64\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
- name: Install msys2 tools
run: |
Start-Process "c:\msys64\usr\bin\pacman.exe" -ArgumentList @("-S", "--noconfirm", "mingw-w64-clang-x86_64-gcc-compat", "mingw-w64-clang-x86_64-clang") -NoNewWindow -Wait
- name: make cuda runner
run: |
import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make cuda_v$(($env:CUDA_PATH | split-path -leaf) -replace 'v(\d+).*', '$1')
runners-cpu:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
if: ${{ needs.changes.outputs.GENERATE == 'True' }}
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-2019]
@ -215,39 +58,178 @@ jobs:
runs-on: ${{ matrix.os }}
env:
GOARCH: ${{ matrix.arch }}
ARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
cache: true
- name: Add msys paths
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
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 msys2 tools
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
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
- name: 'Build Windows Go Runners'
if: ${{ startsWith(matrix.os, 'windows-') }}
run: |
- run: go get ./...
- run: |
$gopath=(get-command go).source | split-path -parent
$gccpath=(get-command gcc).source | split-path -parent
import-module 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Microsoft.VisualStudio.DevShell.dll'
Enter-VsDevShell -vsinstallpath 'C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise' -skipautomaticlocation -DevCmdArguments '-arch=x64 -no_logo'
& "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
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
make -j 4
- name: 'Build Unix Go Runners'
go generate -x ./...
if: ${{ startsWith(matrix.os, 'windows-') }}
name: 'Windows Go Generate'
- run: go generate -x ./...
if: ${{ ! startsWith(matrix.os, 'windows-') }}
run: make -j 4
- run: go build .
name: 'Unix Go Generate'
- 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/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: cuda-${{ matrix.cuda-version }}-libraries
path: |
llm/build/**/bin/*
dist/windows-amd64/**
generate-rocm:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_ROCM == 'True' }}
strategy:
matrix:
rocm-version:
- '6.0.2'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
- run: |
apt-get update && apt-get install -y git build-essential curl rocm-libs
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:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
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: |
$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:
OLLAMA_SKIP_CPU_GENERATE: '1'
# TODO - do we need any artifacts?
# CUDA generation step
generate-windows-cuda:
needs: [changes]
if: ${{ needs.changes.outputs.GENERATE_CUDA == 'True' }}
runs-on: windows
steps:
- uses: actions/checkout@v4
- 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"
$env:OLLAMA_SKIP_CPU_GENERATE="1"
go generate -x ./...
env:
OLLAMA_SKIP_CPU_GENERATE: '1'
# TODO - do we need any artifacts?
lint:
strategy:
@ -279,9 +261,17 @@ jobs:
arm64) echo ARCH=arm64 ;;
esac >>$GITHUB_ENV
shell: bash
- uses: golangci/golangci-lint-action@v6
- 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@v4
with:
args: --timeout 10m0s -v
args: --timeout 8m0s -v
test:
strategy:
matrix:
@ -296,6 +286,9 @@ jobs:
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
OLLAMA_CPU_TARGET: 'static'
OLLAMA_SKIP_CPU_GENERATE: '1'
OLLAMA_SKIP_METAL_GENERATE: '1'
steps:
- uses: actions/checkout@v4
with:
@ -306,21 +299,23 @@ jobs:
cache: true
- run: |
case ${{ matrix.arch }} in
amd64) echo ARCH=amd64 ;;
amd64) echo ARCH=x86_64 ;;
arm64) echo ARCH=arm64 ;;
esac >>$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 ./...
patches:
needs: [changes]
if: ${{ needs.changes.outputs.RUNNERS == 'True' }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/upload-artifact@v4
with:
submodules: recursive
- name: Verify patches carry all the changes
run: |
make apply-patches sync && git diff --compact-summary --exit-code llama
name: ${{ matrix.os }}-binaries
path: ollama

7
.gitignore vendored
View File

@ -5,14 +5,11 @@
.swp
dist
ollama
ggml-metal.metal
.cache
*.exe
.idea
test_data
*.crt
llm/build
build/*/*/*
!build/**/placeholder
llama/build
__debug_bin*
llama/vendor
__debug_bin*

4
.gitmodules vendored Normal file
View File

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

View File

@ -7,41 +7,11 @@ linters:
- bodyclose
- containedctx
- contextcheck
- errcheck
- exportloopref
- gci
- gocheckcompilerdirectives
- gofmt
- gofumpt
- gosimple
- govet
- ineffassign
- intrange
- makezero
# FIXME: for some reason this errors on windows
# - gofmt
# - goimports
- misspell
- nilerr
- nolintlint
- nosprintfhostport
- staticcheck
- tenv
- unconvert
- unused
- usestdlibvars
- wastedassign
- whitespace
linters-settings:
gci:
sections: [standard, default, localmodule]
staticcheck:
checks:
- all
- -SA1019 # omit Deprecated check
severity:
default-severity: error
rules:
- linters:
- gofmt
- goimports
- intrange
- usestdlibvars
severity: info

View File

@ -1,37 +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.
## Pull requests
### Ideal issues
* [Bugs](https://github.com/ollama/ollama/issues?q=is%3Aissue+is%3Aopen+label%3Abug): issues where Ollama stops working or where it results in an unexpected error.
* [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
### Best practices
* Commit messages: please leave both a title and a description in your commit messages. The title should be a short summary of the changes, with a leading word that explains the section of the code being changed (e.g. `api: fix parsing of prompt field`) . In the description, leave a short 2-3 sentences that explain more about the change and its impact.
* Tests: please add test coverage to changes where possible.
* Minimize dependencies: avoid adding new dependencies unless absolutely necessary.
## Need help?
If you need help with anything, feel free to reach out to us on our [Discord server](https://discord.gg/ollama).

View File

@ -1,263 +1,131 @@
ARG GOLANG_VERSION=1.22.8
ARG GOLANG_VERSION=1.22.1
ARG CMAKE_VERSION=3.22.1
ARG CUDA_VERSION_11=11.3.1
ARG CUDA_V11_ARCHITECTURES="50;52;53;60;61;62;70;72;75;80;86"
ARG CUDA_VERSION_12=12.4.0
ARG CUDA_V12_ARCHITECTURES="60;61;62;70;72;75;80;86;87;89;90;90a"
ARG ROCM_VERSION=6.1.2
ARG JETPACK_6=r36.2.0
ARG JETPACK_5=r35.4.1
# this CUDA_VERSION corresponds with the one specified in docs/gpu.md
ARG CUDA_VERSION=11.3.1
ARG ROCM_VERSION=6.0.2
### To create a local image for building linux binaries on mac or windows with efficient incremental builds
#
# docker build --platform linux/amd64 -t builder-amd64 -f Dockerfile --target unified-builder-amd64 .
# docker run --platform linux/amd64 --rm -it -v $(pwd):/go/src/github.com/ollama/ollama/ builder-amd64
#
### Then incremental builds will be much faster in this container
#
# make -j 10 && go build -trimpath -o dist/linux-amd64/ollama .
#
FROM --platform=linux/amd64 rocm/dev-centos-7:${ROCM_VERSION}-complete AS unified-builder-amd64
# 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
FROM --platform=linux/amd64 nvidia/cuda:$CUDA_VERSION-devel-centos7 AS cuda-build-amd64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
ARG CUDA_VERSION_11
ARG CUDA_VERSION_12
COPY ./scripts/rh_linux_deps.sh /
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:/usr/local/cuda/bin:$PATH
ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:/opt/amdgpu/lib64
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
RUN yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo && \
dnf clean all && \
dnf install -y \
zsh \
cuda-$(echo ${CUDA_VERSION_11} | cut -f1-2 -d. | sed -e "s/\./-/g") \
cuda-$(echo ${CUDA_VERSION_12} | cut -f1-2 -d. | sed -e "s/\./-/g")
# TODO intel oneapi goes here...
ENV GOARCH amd64
ENV CGO_ENABLED 1
WORKDIR /go/src/github.com/ollama/ollama/
ENTRYPOINT [ "zsh" ]
RUN CMAKE_VERSION=${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
### To create a local image for building linux binaries on mac or linux/arm64 with efficient incremental builds
# Note: this does not contain jetson variants
#
# docker build --platform linux/arm64 -t builder-arm64 -f Dockerfile --target unified-builder-arm64 .
# docker run --platform linux/arm64 --rm -it -v $(pwd):/go/src/github.com/ollama/ollama/ builder-arm64
#
FROM --platform=linux/arm64 rockylinux:8 AS unified-builder-arm64
FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION-devel-rockylinux8 AS cuda-build-arm64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
ARG CUDA_VERSION_11
ARG CUDA_VERSION_12
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
RUN yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/sbsa/cuda-rhel8.repo && \
dnf config-manager --set-enabled appstream && \
dnf clean all && \
dnf install -y \
zsh \
cuda-toolkit-$(echo ${CUDA_VERSION_11} | cut -f1-2 -d. | sed -e "s/\./-/g") \
cuda-toolkit-$(echo ${CUDA_VERSION_12} | cut -f1-2 -d. | sed -e "s/\./-/g")
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH:/usr/local/cuda/bin
ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:/opt/amdgpu/lib64
ENV GOARCH amd64
ENV CGO_ENABLED 1
WORKDIR /go/src/github.com/ollama/ollama/
ENTRYPOINT [ "zsh" ]
FROM --platform=linux/amd64 unified-builder-amd64 AS runners-amd64
COPY . .
ARG OLLAMA_SKIP_CUDA_GENERATE
ARG OLLAMA_SKIP_CUDA_11_GENERATE
ARG OLLAMA_SKIP_CUDA_12_GENERATE
ARG OLLAMA_SKIP_ROCM_GENERATE
ARG CUDA_V11_ARCHITECTURES
ARG CUDA_V12_ARCHITECTURES
ARG OLLAMA_FAST_BUILD
RUN --mount=type=cache,target=/root/.ccache \
if grep "^flags" /proc/cpuinfo|grep avx>/dev/null; then \
make -j $(expr $(nproc) / 2 ) ; \
else \
make -j 5 ; \
fi
FROM --platform=linux/arm64 unified-builder-arm64 AS runners-arm64
COPY . .
ARG OLLAMA_SKIP_CUDA_GENERATE
ARG OLLAMA_SKIP_CUDA_11_GENERATE
ARG OLLAMA_SKIP_CUDA_12_GENERATE
ARG CUDA_V11_ARCHITECTURES
ARG CUDA_V12_ARCHITECTURES
ARG OLLAMA_FAST_BUILD
RUN --mount=type=cache,target=/root/.ccache \
make -j 5
# Jetsons need to be built in discrete stages
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_5} AS runners-jetpack5-arm64
ARG GOLANG_VERSION
RUN apt-get update && apt-get install -y git curl ccache && \
curl -s -L https://dl.google.com/go/go${GOLANG_VERSION}.linux-arm64.tar.gz | tar xz -C /usr/local && \
ln -s /usr/local/go/bin/go /usr/local/bin/go && \
ln -s /usr/local/go/bin/gofmt /usr/local/bin/gofmt && \
apt-get clean && rm -rf /var/lib/apt/lists/*
WORKDIR /go/src/github.com/ollama/ollama/
COPY . .
RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
ARG CGO_CFLAGS
ENV GOARCH arm64
RUN --mount=type=cache,target=/root/.ccache \
make -j 5 cuda_v11 \
CUDA_ARCHITECTURES="72;87" \
GPU_RUNNER_VARIANT=_jetpack5 \
CGO_EXTRA_LDFLAGS_LINUX=-L/usr/local/cuda/lib64/stubs \
DIST_LIB_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ollama \
DIST_GPU_RUNNER_DEPS_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ollama/cuda_jetpack5
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
FROM --platform=linux/arm64 nvcr.io/nvidia/l4t-jetpack:${JETPACK_6} AS runners-jetpack6-arm64
ARG GOLANG_VERSION
RUN apt-get update && apt-get install -y git curl ccache && \
curl -s -L https://dl.google.com/go/go${GOLANG_VERSION}.linux-arm64.tar.gz | tar xz -C /usr/local && \
ln -s /usr/local/go/bin/go /usr/local/bin/go && \
ln -s /usr/local/go/bin/gofmt /usr/local/bin/gofmt && \
apt-get clean && rm -rf /var/lib/apt/lists/*
WORKDIR /go/src/github.com/ollama/ollama/
COPY . .
FROM --platform=linux/amd64 rocm/dev-centos-7:${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
ENV GOARCH arm64
RUN --mount=type=cache,target=/root/.ccache \
make -j 5 cuda_v12 \
CUDA_ARCHITECTURES="87" \
GPU_RUNNER_VARIANT=_jetpack6 \
CGO_EXTRA_LDFLAGS_LINUX=-L/usr/local/cuda/lib64/stubs \
DIST_LIB_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ollama \
DIST_GPU_RUNNER_DEPS_DIR=/go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ollama/cuda_jetpack6
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 ${dep} /tmp/scratch/ || exit 1 ; \
done && \
(cd /opt/rocm/lib && tar cf - rocblas/library) | (cd /tmp/scratch/ && tar xf - ) && \
mkdir -p /go/src/github.com/ollama/ollama/dist/deps/ && \
(cd /tmp/scratch/ && tar czvf /go/src/github.com/ollama/ollama/dist/deps/ollama-linux-amd64-rocm.tgz . )
# Intermediate stages used for ./scripts/build_linux.sh
FROM --platform=linux/amd64 centos:7 AS builder-amd64
FROM --platform=linux/amd64 centos:7 AS cpu-builder-amd64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
ENV CGO_ENABLED 1
ENV GOARCH amd64
WORKDIR /go/src/github.com/ollama/ollama
FROM --platform=linux/amd64 builder-amd64 AS build-amd64
COPY . .
COPY --from=runners-amd64 /go/src/github.com/ollama/ollama/dist/ dist/
COPY --from=runners-amd64 /go/src/github.com/ollama/ollama/build/ build/
ARG GOFLAGS
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
ARG OLLAMA_SKIP_ROCM_GENERATE
RUN --mount=type=cache,target=/root/.ccache \
go build -trimpath -o dist/linux-amd64/bin/ollama .
RUN cd dist/linux-$GOARCH && \
tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH.tgz
RUN if [ -z ${OLLAMA_SKIP_ROCM_GENERATE} ] ; then \
cd dist/linux-$GOARCH-rocm && \
tar -cf - . | pigz --best > ../ollama-linux-$GOARCH-rocm.tgz ;\
fi
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
FROM --platform=linux/arm64 rockylinux:8 AS builder-arm64
FROM --platform=linux/amd64 cpu-builder-amd64 AS static-build-amd64
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu-build-amd64
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx-build-amd64
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
FROM --platform=linux/arm64 centos:7 AS cpu-builder-arm64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS
WORKDIR /go/src/github.com/ollama/ollama/llm/generate
FROM --platform=linux/arm64 cpu-builder-arm64 AS static-build-arm64
RUN OLLAMA_CPU_TARGET="static" sh gen_linux.sh
FROM --platform=linux/arm64 cpu-builder-arm64 AS cpu-build-arm64
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
# Intermediate stage used for ./scripts/build_linux.sh
FROM --platform=linux/amd64 cpu-build-amd64 AS build-amd64
ENV CGO_ENABLED 1
ENV GOARCH arm64
WORKDIR /go/src/github.com/ollama/ollama
FROM --platform=linux/arm64 builder-arm64 AS build-arm64
COPY . .
COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
COPY --from=runners-arm64 /go/src/github.com/ollama/ollama/build/ build/
COPY --from=runners-jetpack5-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
COPY --from=runners-jetpack5-arm64 /go/src/github.com/ollama/ollama/build/ build/
COPY --from=runners-jetpack6-arm64 /go/src/github.com/ollama/ollama/dist/ dist/
COPY --from=runners-jetpack6-arm64 /go/src/github.com/ollama/ollama/build/ build/
ARG GOFLAGS
ARG CGO_CFLAGS
RUN --mount=type=cache,target=/root/.ccache \
go build -trimpath -o dist/linux-arm64/bin/ollama .
RUN cd dist/linux-$GOARCH && \
tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH.tgz
RUN cd dist/linux-$GOARCH-jetpack5 && \
tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH-jetpack5.tgz
RUN cd dist/linux-$GOARCH-jetpack6 && \
tar --exclude runners -cf - . | pigz --best > ../ollama-linux-$GOARCH-jetpack6.tgz
FROM --platform=linux/amd64 scratch AS dist-amd64
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/ollama-linux-*.tgz /
FROM --platform=linux/arm64 scratch AS dist-arm64
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/ollama-linux-*.tgz /
FROM dist-$TARGETARCH AS dist
# Optimized container images do not cary nested payloads
FROM --platform=linux/amd64 builder-amd64 AS container-build-amd64
WORKDIR /go/src/github.com/ollama/ollama
COPY . .
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 --mount=type=cache,target=/root/.ccache \
go build -trimpath -o dist/linux-amd64/bin/ollama .
RUN go build -trimpath .
FROM --platform=linux/arm64 builder-arm64 AS container-build-arm64
# 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 --mount=type=cache,target=/root/.ccache \
go build -trimpath -o dist/linux-arm64/bin/ollama .
RUN go build -trimpath .
# For amd64 container images, filter out cuda/rocm to minimize size
FROM runners-amd64 AS runners-cuda-amd64
RUN rm -rf \
./dist/linux-amd64/lib/ollama/libggml_hipblas.so \
./dist/linux-amd64/lib/ollama/runners/rocm*
FROM runners-amd64 AS runners-rocm-amd64
RUN rm -rf \
./dist/linux-amd64/lib/ollama/libggml_cuda*.so \
./dist/linux-amd64/lib/ollama/libcu*.so* \
./dist/linux-amd64/lib/ollama/runners/cuda*
FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-amd64
RUN apt-get update && \
apt-get install -y ca-certificates && \
apt-get clean && rm -rf /var/lib/apt/lists/*
COPY --from=container-build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
COPY --from=runners-cuda-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
FROM --platform=linux/arm64 ubuntu:22.04 AS runtime-arm64
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack5/lib/ /lib/
COPY --from=build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64-jetpack6/lib/ /lib/
RUN apt-get update && \
apt-get install -y ca-certificates && \
apt-get clean && rm -rf /var/lib/apt/lists/*
COPY --from=container-build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/bin/ /bin/
COPY --from=cpu-build-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
COPY --from=cuda-11-build-runner-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
COPY --from=cuda-12-build-runner-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
COPY --from=cuda-build-jetpack5-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
COPY --from=cuda-build-jetpack6-arm64 /go/src/github.com/ollama/ollama/dist/linux-arm64/lib/ /lib/
# ROCm libraries larger so we keep it distinct from the CPU/CUDA image
FROM --platform=linux/amd64 ubuntu:22.04 AS runtime-rocm
# Frontload the rocm libraries which are large, and rarely change to increase chance of a common layer
# across releases
COPY --from=build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64-rocm/lib/ /lib/
RUN apt-get update && \
apt-get install -y ca-certificates && \
apt-get clean && rm -rf /var/lib/apt/lists/*
COPY --from=container-build-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/bin/ /bin/
COPY --from=runners-rocm-amd64 /go/src/github.com/ollama/ollama/dist/linux-amd64/lib/ /lib/
# 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
# 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

View File

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

159
README.md
View File

@ -6,13 +6,13 @@
[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
Get up and running with large language models.
Get up and running with large language models locally.
### macOS
[Download](https://ollama.com/download/Ollama-darwin.zip)
### Windows
### Windows preview
[Download](https://ollama.com/download/OllamaSetup.exe)
@ -35,10 +35,10 @@ The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `olla
## 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):
```
ollama run llama3.2
ollama run llama3
```
## Model library
@ -47,31 +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 |
| ------------------ | ---------- | ----- | -------------------------------- |
| 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 | 70B | 40GB | `ollama run llama3.1:70b` |
| Llama 3.1 | 405B | 231GB | `ollama run llama3.1:405b` |
| Phi 3 Mini | 3.8B | 2.3GB | `ollama run phi3` |
| Phi 3 Medium | 14B | 7.9GB | `ollama run phi3:medium` |
| Gemma 2 | 2B | 1.6GB | `ollama run gemma2:2b` |
| Gemma 2 | 9B | 5.5GB | `ollama run gemma2` |
| Gemma 2 | 27B | 16GB | `ollama run gemma2:27b` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| Moondream 2 | 1.4B | 829MB | `ollama run moondream` |
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
| Starling | 7B | 4.1GB | `ollama run starling-lm` |
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
| LLaVA | 7B | 4.5GB | `ollama run llava` |
| Solar | 10.7B | 6.1GB | `ollama run solar` |
| 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 | 2B | 1.4GB | `ollama run gemma:2b` |
| Gemma | 7B | 4.8GB | `ollama run gemma:7b` |
| 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
@ -103,16 +96,16 @@ 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:
```
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
@ -147,7 +140,7 @@ ollama create mymodel -f ./Modelfile
### Pull a model
```
ollama pull llama3.2
ollama pull llama3
```
> This command can also be used to update a local model. Only the diff will be pulled.
@ -155,13 +148,13 @@ ollama pull llama3.2
### Remove a model
```
ollama rm llama3.2
ollama rm llama3
```
### Copy a model
```
ollama cp llama3.2 my-model
ollama cp llama3 my-model
```
### Multiline input
@ -178,41 +171,23 @@ 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.
```
### Pass the prompt as an argument
```
$ ollama run llama3.2 "Summarize this file: $(cat README.md)"
$ 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
```
ollama show llama3.2
```
### List models on your computer
```
ollama list
```
### List which models are currently loaded
```
ollama ps
```
### Stop a model which is currently running
```
ollama stop llama3.2
```
### Start Ollama
`ollama serve` is used when you want to start ollama without running the desktop application.
@ -232,7 +207,7 @@ Next, start the server:
Finally, in a separate shell, run a model:
```
./ollama run llama3.2
./ollama run llama3
```
## REST API
@ -243,7 +218,7 @@ Ollama has a REST API for running and managing models.
```
curl http://localhost:11434/api/generate -d '{
"model": "llama3.2",
"model": "llama3",
"prompt":"Why is the sky blue?"
}'
```
@ -252,7 +227,7 @@ curl http://localhost:11434/api/generate -d '{
```
curl http://localhost:11434/api/chat -d '{
"model": "llama3.2",
"model": "llama3",
"messages": [
{ "role": "user", "content": "why is the sky blue?" }
]
@ -310,31 +285,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [macai](https://github.com/Renset/macai) (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
- [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
- [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)
- [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)
- [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)
- [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)
- [LLMChat](https://github.com/trendy-design/llmchat) (Privacy focused, 100% local, intuitive all-in-one chat interface)
- [ARGO](https://github.com/xark-argo/argo) (Locally download and run Ollama and Huggingface models with RAG on Mac/Windows/Linux)
- [G1](https://github.com/bklieger-groq/g1) (Prototype of using prompting strategies to improve the LLM's reasoning through o1-like reasoning chains.)
- [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)
- [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)
### Terminal
@ -357,14 +307,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [ShellOracle](https://github.com/djcopley/ShellOracle)
- [tlm](https://github.com/yusufcanb/tlm)
- [podman-ollama](https://github.com/ericcurtin/podman-ollama)
- [gollama](https://github.com/sammcj/gollama)
- [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
- [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.
### Apple Vision Pro
- [Enchanted](https://github.com/AugustDev/enchanted)
### Database
@ -374,28 +316,20 @@ See the [API documentation](./docs/api.md) for all endpoints.
### Package managers
- [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/)
- [Gentoo](https://github.com/gentoo/guru/tree/master/app-misc/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?channel=24.05&show=ollama&from=0&size=50&sort=relevance&type=packages&query=ollama)
- [Flox](https://flox.dev/blog/ollama-part-one)
### Libraries
- [LangChain](https://python.langchain.com/docs/integrations/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)
- [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)
- [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)
@ -412,20 +346,10 @@ 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)
- [Gollm](https://docs.gollm.co/examples/ollama-example)
- [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)
- [Ollama for Swift](https://github.com/mattt/ollama-swift)
- [GoLamify](https://github.com/prasad89/golamify)
### Mobile
- [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)
### Extensions & Plugins
@ -448,22 +372,13 @@ 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)
- [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)
- [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/jk011ru/vnc-lm) (A containerized Discord bot with support for attachments and web links)
- [LSP-AI](https://github.com/SilasMarvin/lsp-ai) (Open-source language server for AI-powered functionality)
- [QodeAssist](https://github.com/Palm1r/QodeAssist) (AI-powered coding assistant plugin for Qt Creator)
- [Obsidian Quiz Generator plugin](https://github.com/ECuiDev/obsidian-quiz-generator)
- [TextCraft](https://github.com/suncloudsmoon/TextCraft) (Copilot in Word alternative using Ollama)
### Supported backends
### Supported backends
- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.

View File

@ -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

View File

@ -18,14 +18,16 @@ import (
"bytes"
"context"
"encoding/json"
"errors"
"fmt"
"io"
"net"
"net/http"
"net/url"
"os"
"runtime"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/version"
)
@ -55,7 +57,7 @@ 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>
@ -63,12 +65,66 @@ 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, err := GetOllamaHost()
if err != nil {
return nil, err
}
return &Client{
base: envconfig.Host(),
base: &url.URL{
Scheme: ollamaHost.Scheme,
Host: net.JoinHostPort(ollamaHost.Host, ollamaHost.Port),
},
http: http.DefaultClient,
}, nil
}
type OllamaHost struct {
Scheme string
Host string
Port string
}
func GetOllamaHost() (OllamaHost, error) {
defaultPort := "11434"
hostVar := os.Getenv("OLLAMA_HOST")
hostVar = strings.TrimSpace(strings.Trim(strings.TrimSpace(hostVar), "\"'"))
scheme, hostport, ok := strings.Cut(hostVar, "://")
switch {
case !ok:
scheme, hostport = "http", hostVar
case scheme == "http":
defaultPort = "80"
case scheme == "https":
defaultPort = "443"
}
// trim trailing slashes
hostport = strings.TrimRight(hostport, "/")
host, port, err := net.SplitHostPort(hostport)
if err != nil {
host, port = "127.0.0.1", defaultPort
if ip := net.ParseIP(strings.Trim(hostport, "[]")); ip != nil {
host = ip.String()
} else if hostport != "" {
host = hostport
}
}
if portNum, err := strconv.ParseInt(port, 10, 32); err != nil || portNum > 65535 || portNum < 0 {
return OllamaHost{}, ErrInvalidHostPort
}
return OllamaHost{
Scheme: scheme,
Host: host,
Port: port,
}, nil
}
func NewClient(base *url.URL, http *http.Client) *Client {
return &Client{
base: base,
@ -173,7 +229,7 @@ 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 {
@ -298,9 +354,9 @@ func (c *Client) List(ctx context.Context) (*ListResponse, error) {
return &lr, nil
}
// ListRunning lists running models.
func (c *Client) ListRunning(ctx context.Context) (*ProcessResponse, error) {
var lr ProcessResponse
// List running models.
func (c *Client) ListRunning(ctx context.Context) (*ListResponse, error) {
var lr ListResponse
if err := c.do(ctx, http.MethodGet, "/api/ps", nil, &lr); err != nil {
return nil, err
}
@ -333,7 +389,7 @@ 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 +398,7 @@ 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 {

View File

@ -1,7 +1,11 @@
package api
import (
"fmt"
"net"
"testing"
"github.com/stretchr/testify/assert"
)
func TestClientFromEnvironment(t *testing.T) {
@ -42,4 +46,40 @@ func TestClientFromEnvironment(t *testing.T) {
}
})
}
hostTestCases := map[string]*testCase{
"empty": {value: "", expect: "127.0.0.1:11434"},
"only address": {value: "1.2.3.4", expect: "1.2.3.4:11434"},
"only port": {value: ":1234", expect: ":1234"},
"address and port": {value: "1.2.3.4:1234", expect: "1.2.3.4:1234"},
"hostname": {value: "example.com", expect: "example.com:11434"},
"hostname and port": {value: "example.com:1234", expect: "example.com:1234"},
"zero port": {value: ":0", expect: ":0"},
"too large port": {value: ":66000", err: ErrInvalidHostPort},
"too small port": {value: ":-1", err: ErrInvalidHostPort},
"ipv6 localhost": {value: "[::1]", expect: "[::1]:11434"},
"ipv6 world open": {value: "[::]", expect: "[::]:11434"},
"ipv6 no brackets": {value: "::1", expect: "[::1]:11434"},
"ipv6 + port": {value: "[::1]:1337", expect: "[::1]:1337"},
"extra space": {value: " 1.2.3.4 ", expect: "1.2.3.4:11434"},
"extra quotes": {value: "\"1.2.3.4\"", expect: "1.2.3.4:11434"},
"extra space+quotes": {value: " \" 1.2.3.4 \" ", expect: "1.2.3.4:11434"},
"extra single quotes": {value: "'1.2.3.4'", expect: "1.2.3.4:11434"},
}
for k, v := range hostTestCases {
t.Run(k, func(t *testing.T) {
t.Setenv("OLLAMA_HOST", v.value)
oh, err := GetOllamaHost()
if err != v.err {
t.Fatalf("expected %s, got %s", v.err, err)
}
if err == nil {
host := net.JoinHostPort(oh.Host, oh.Port)
assert.Equal(t, v.expect, host, fmt.Sprintf("%s: expected %s, got %s", k, v.expect, host))
}
})
}
}

View File

@ -2,6 +2,7 @@ package api
import (
"encoding/json"
"errors"
"fmt"
"log/slog"
"math"
@ -12,7 +13,7 @@ import (
"time"
)
// 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
@ -47,9 +48,6 @@ 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"`
@ -57,7 +55,7 @@ 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.
@ -90,95 +88,27 @@ 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 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]interface{} `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)
}
// 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 {
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
@ -203,8 +133,8 @@ 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
@ -214,7 +144,6 @@ 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"`
@ -231,45 +160,18 @@ type Options struct {
// Runner options which must be set when the model is loaded into memory
type Runner struct {
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
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap *bool `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
// 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]interface{} `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"`
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"`
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap bool `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
// EmbeddingRequest is the request passed to [Client.Embeddings].
@ -296,17 +198,15 @@ type EmbeddingResponse struct {
// CreateRequest is the request passed to [Client.Create].
type CreateRequest struct {
Model string `json:"model"`
Path string `json:"path"`
Modelfile string `json:"modelfile"`
Stream *bool `json:"stream,omitempty"`
Quantize string `json:"quantize,omitempty"`
// Deprecated: set the model name with Model instead
// Name is deprecated, see Model
Name string `json:"name"`
// Deprecated: set the file content with Modelfile instead
Path string `json:"path"`
// Deprecated: use Quantize instead
// Quantization is deprecated, see Quantize
Quantization string `json:"quantization,omitempty"`
}
@ -314,37 +214,31 @@ 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]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"`
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"`
}
// CopyRequest is the request passed to [Client.Copy].
@ -361,7 +255,7 @@ type PullRequest 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"`
}
@ -382,46 +276,25 @@ 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"`
}
// ListResponse is the response from [Client.List].
type ListResponse struct {
Models []ListModelResponse `json:"models"`
Models []ModelResponse `json:"models"`
}
// ProcessResponse is the response from [Client.Process].
type ProcessResponse struct {
Models []ProcessModelResponse `json:"models"`
}
// ListModelResponse is a single model description in [ListResponse].
type ListModelResponse struct {
// ModelResponse is a single model description in [ListResponse].
type ModelResponse struct {
Name string `json:"name"`
Model string `json:"model"`
ModifiedAt time.Time `json:"modified_at"`
ModifiedAt time.Time `json:"modified_at,omitempty"`
Size int64 `json:"size"`
Digest string `json:"digest"`
Details ModelDetails `json:"details,omitempty"`
}
// ProcessModelResponse is a single model description in [ProcessResponse].
type ProcessModelResponse struct {
Name string `json:"name"`
Model string `json:"model"`
Size int64 `json:"size"`
Digest string `json:"digest"`
Details ModelDetails `json:"details,omitempty"`
ExpiresAt time.Time `json:"expires_at"`
SizeVRAM int64 `json:"size_vram"`
}
type RetrieveModelResponse struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
OwnedBy string `json:"owned_by"`
ExpiresAt time.Time `json:"expires_at,omitempty"`
SizeVRAM int64 `json:"size_vram,omitempty"`
}
type TokenResponse struct {
@ -433,7 +306,7 @@ type GenerateResponse struct {
// Model is the model name that generated the response.
Model string `json:"model"`
// CreatedAt is the timestamp of the response.
//CreatedAt is the timestamp of the response.
CreatedAt time.Time `json:"created_at"`
// Response is the textual response itself.
@ -490,6 +363,8 @@ func (m *Metrics) Summary() {
}
}
var ErrInvalidHostPort = errors.New("invalid port specified in OLLAMA_HOST")
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
@ -506,7 +381,7 @@ func (opts *Options) FromMap(m map[string]interface{}) 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
}
@ -562,17 +437,6 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
slice[i] = str
}
field.Set(reflect.ValueOf(slice))
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
field.Set(reflect.ValueOf(&val))
} else {
return fmt.Errorf("unknown type loading config params: %v %v", field.Kind(), field.Type())
}
default:
return fmt.Errorf("unknown type loading config params: %v", field.Kind())
}
@ -613,8 +477,10 @@ func DefaultOptions() Options {
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,
UseMMap: true,
UseNUMA: false,
},
}
}
@ -710,17 +576,6 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
case reflect.Slice:
// TODO: only string slices are supported right now
out[key] = vals
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
return nil, fmt.Errorf("invalid bool value %s", vals)
}
out[key] = &boolVal
} else {
return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
}
default:
return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
}

View File

@ -2,7 +2,6 @@ package api
import (
"encoding/json"
"errors"
"math"
"testing"
"time"
@ -73,13 +72,13 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
},
{
"positive duration",
42 * time.Second,
42 * time.Second,
time.Duration(42 * time.Second),
time.Duration(42 * time.Second),
},
{
"another positive duration",
42 * time.Minute,
42 * time.Minute,
time.Duration(42 * time.Minute),
time.Duration(42 * time.Minute),
},
{
"zero duration",
@ -106,128 +105,3 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
})
}
}
func TestUseMmapParsingFromJSON(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req string
exp *bool
}{
{
name: "Undefined",
req: `{ }`,
exp: nil,
},
{
name: "True",
req: `{ "use_mmap": true }`,
exp: &tr,
},
{
name: "False",
req: `{ "use_mmap": false }`,
exp: &fa,
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
var oMap map[string]interface{}
err := json.Unmarshal([]byte(test.req), &oMap)
require.NoError(t, err)
opts := DefaultOptions()
err = opts.FromMap(oMap)
require.NoError(t, err)
assert.Equal(t, test.exp, opts.UseMMap)
})
}
}
func TestUseMmapFormatParams(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req map[string][]string
exp *bool
err error
}{
{
name: "True",
req: map[string][]string{
"use_mmap": {"true"},
},
exp: &tr,
err: nil,
},
{
name: "False",
req: map[string][]string{
"use_mmap": {"false"},
},
exp: &fa,
err: nil,
},
{
name: "Numeric True",
req: map[string][]string{
"use_mmap": {"1"},
},
exp: &tr,
err: nil,
},
{
name: "Numeric False",
req: map[string][]string{
"use_mmap": {"0"},
},
exp: &fa,
err: nil,
},
{
name: "invalid string",
req: map[string][]string{
"use_mmap": {"foo"},
},
exp: nil,
err: errors.New("invalid bool value [foo]"),
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
resp, err := FormatParams(test.req)
require.Equal(t, test.err, err)
respVal, ok := resp["use_mmap"]
if test.exp != nil {
assert.True(t, ok, "resp: %v", resp)
assert.Equal(t, *test.exp, *respVal.(*bool))
}
})
}
}
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)
}
}
}

View File

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

View File

@ -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)
}

View File

@ -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

View File

@ -5,8 +5,6 @@ import (
"log/slog"
"os"
"path/filepath"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
)
@ -14,7 +12,7 @@ import (
func InitLogging() {
level := slog.LevelInfo
if envconfig.Debug() {
if envconfig.Debug {
level = slog.LevelDebug
}
@ -26,8 +24,7 @@ func InitLogging() {
logFile = os.Stderr
// 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
@ -49,32 +46,3 @@ func InitLogging() {
slog.Info("ollama app started")
}
func rotateLogs(logFile string) {
if _, err := os.Stat(logFile); os.IsNotExist(err) {
return
}
index := strings.LastIndex(logFile, ".")
pre := logFile[:index]
post := "." + logFile[index+1:]
for i := LogRotationCount; i > 0; i-- {
older := pre + "-" + strconv.Itoa(i) + post
newer := pre + "-" + strconv.Itoa(i-1) + post
if i == 1 {
newer = pre + post
}
if _, err := os.Stat(newer); err == nil {
if _, err := os.Stat(older); err == nil {
err := os.Remove(older)
if err != nil {
slog.Warn("Failed to remove older log", "older", older, "error", err)
continue
}
}
err := os.Rename(newer, older)
if err != nil {
slog.Warn("Failed to rotate log", "older", older, "newer", newer, "error", err)
}
}
}
}

View File

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

View File

@ -1,44 +0,0 @@
package lifecycle
import (
"os"
"path/filepath"
"strconv"
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestRotateLogs(t *testing.T) {
logDir := t.TempDir()
logFile := filepath.Join(logDir, "testlog.log")
// No log exists
rotateLogs(logFile)
require.NoError(t, os.WriteFile(logFile, []byte("1"), 0o644))
assert.FileExists(t, logFile)
// First rotation
rotateLogs(logFile)
assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
assert.NoFileExists(t, logFile)
// Should be a no-op without a new log
rotateLogs(logFile)
assert.FileExists(t, filepath.Join(logDir, "testlog-1.log"))
assert.NoFileExists(t, filepath.Join(logDir, "testlog-2.log"))
assert.NoFileExists(t, logFile)
for i := 2; i <= LogRotationCount+1; i++ {
require.NoError(t, os.WriteFile(logFile, []byte(strconv.Itoa(i)), 0o644))
assert.FileExists(t, logFile)
rotateLogs(logFile)
assert.NoFileExists(t, logFile)
for j := 1; j < i; j++ {
assert.FileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(j)+".log"))
}
assert.NoFileExists(t, filepath.Join(logDir, "testlog-"+strconv.Itoa(i+1)+".log"))
}
}

View File

@ -16,12 +16,11 @@ var (
AppDir = "/opt/Ollama"
AppDataDir = "/opt/Ollama"
// TODO - should there be a distinct log dir?
UpdateStageDir = "/tmp"
AppLogFile = "/tmp/ollama_app.log"
ServerLogFile = "/tmp/ollama.log"
UpgradeLogFile = "/tmp/ollama_update.log"
Installer = "OllamaSetup.exe"
LogRotationCount = 5
UpdateStageDir = "/tmp"
AppLogFile = "/tmp/ollama_app.log"
ServerLogFile = "/tmp/ollama.log"
UpgradeLogFile = "/tmp/ollama_update.log"
Installer = "OllamaSetup.exe"
)
func init() {
@ -36,13 +35,8 @@ 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"), ";")
@ -69,12 +63,13 @@ 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))
}
}
} else if runtime.GOOS == "darwin" {
// TODO
AppName += ".app"

View File

@ -15,20 +15,14 @@ import (
)
func getCLIFullPath(command string) string {
var cmdPath string
cmdPath := ""
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 {
@ -60,8 +54,8 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
return nil, fmt.Errorf("failed to spawn server stderr pipe: %w", err)
}
rotateLogs(ServerLogFile)
logFile, err := os.OpenFile(ServerLogFile, os.O_APPEND|os.O_WRONLY|os.O_CREATE, 0o755)
// TODO - rotation
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)
}
@ -71,6 +65,7 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
if err != nil {
if !errors.Is(err, os.ErrNotExist) {
return nil, fmt.Errorf("stat ollama server log dir %s: %v", logDir, err)
}
if err := os.MkdirAll(logDir, 0o755); err != nil {

View File

@ -24,8 +24,7 @@ func terminate(cmd *exec.Cmd) error {
if err != nil {
return err
}
//nolint:errcheck
defer dll.Release()
defer dll.Release() // nolint: errcheck
pid := cmd.Process.Pid
@ -74,8 +73,7 @@ func isProcessExited(pid int) (bool, error) {
if err != nil {
return false, fmt.Errorf("failed to open process: %v", err)
}
//nolint:errcheck
defer windows.CloseHandle(hProcess)
defer windows.CloseHandle(hProcess) // nolint: errcheck
var exitCode uint32
err = windows.GetExitCodeProcess(hProcess, &exitCode)

View File

@ -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 {
@ -79,7 +78,7 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
}
defer resp.Body.Close()
if resp.StatusCode == http.StatusNoContent {
if resp.StatusCode == 204 {
slog.Debug("check update response 204 (current version is up to date)")
return false, updateResp
}
@ -88,7 +87,7 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
slog.Warn(fmt.Sprintf("failed to read body response: %s", err))
}
if resp.StatusCode != http.StatusOK {
if resp.StatusCode != 200 {
slog.Info(fmt.Sprintf("check update error %d - %.96s", resp.StatusCode, string(body)))
return false, updateResp
}
@ -115,7 +114,7 @@ func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
if err != nil {
return fmt.Errorf("error checking update: %w", err)
}
if resp.StatusCode != http.StatusOK {
if resp.StatusCode != 200 {
return fmt.Errorf("unexpected status attempting to download update %d", resp.StatusCode)
}
resp.Body.Close()

View File

@ -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")
}

View File

@ -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?

View File

@ -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
@ -87,21 +86,16 @@ 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
Source: "..\dist\windows-arm64\lib\ollama\*"; DestDir: "{app}\lib\ollama\"; Check: IsArm64(); Flags: ignoreversion 64bit recursesubdirs
#endif
Source: ".\app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ; Flags: ignoreversion 64bit
Source: "..\ollama.exe"; DestDir: "{app}"; Flags: ignoreversion 64bit
Source: "..\dist\windows-{#ARCH}\*.dll"; 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\rocm")
Source: "..\dist\windows-amd64\rocm\*"; DestDir: "{app}\rocm\"; Flags: ignoreversion recursesubdirs
#endif
[Icons]
Name: "{group}\{#MyAppName}"; Filename: "{app}\{#MyAppExeName}"; IconFilename: "{app}\app.ico"
@ -109,9 +103,6 @@ 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]
@ -131,18 +122,14 @@ 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]
@ -167,39 +154,3 @@ 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;

View File

@ -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 ""

View File

@ -29,6 +29,7 @@ func GetID() string {
initStore()
}
return store.ID
}
func GetFirstTimeRun() bool {

View File

@ -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")
}

View File

@ -11,7 +11,9 @@ import (
"golang.org/x/sys/windows"
)
var quitOnce sync.Once
var (
quitOnce sync.Once
)
func (t *winTray) Run() {
nativeLoop()
@ -45,6 +47,7 @@ func nativeLoop() {
default:
pTranslateMessage.Call(uintptr(unsafe.Pointer(m))) //nolint:errcheck
pDispatchMessage.Call(uintptr(unsafe.Pointer(m))) //nolint:errcheck
}
}
}
@ -157,8 +160,8 @@ func (t *winTray) wndProc(hWnd windows.Handle, message uint32, wParam, lParam ui
lResult, _, _ = pDefWindowProc.Call(
uintptr(hWnd),
uintptr(message),
wParam,
lParam,
uintptr(wParam),
uintptr(lParam),
)
}
return

View File

@ -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 {
@ -36,7 +35,7 @@ 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, updateMenutTitle, false); err != nil {

View File

@ -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
@ -188,7 +186,7 @@ func (t *winTray) initInstance() error {
t.muNID.Lock()
defer t.muNID.Unlock()
t.nid = &notifyIconData{
Wnd: t.window,
Wnd: windows.Handle(t.window),
ID: 100,
Flags: NIF_MESSAGE,
CallbackMessage: t.wmSystrayMessage,
@ -199,6 +197,7 @@ func (t *winTray) initInstance() error {
}
func (t *winTray) createMenu() error {
menuHandle, _, err := pCreatePopupMenu.Call()
if menuHandle == 0 {
return err
@ -247,7 +246,7 @@ func (t *winTray) addOrUpdateMenuItem(menuItemId uint32, parentId uint32, title
mi := menuItemInfo{
Mask: MIIM_FTYPE | MIIM_STRING | MIIM_ID | MIIM_STATE,
Type: MFT_STRING,
ID: menuItemId,
ID: uint32(menuItemId),
TypeData: titlePtr,
Cch: uint32(len(title)),
}
@ -303,10 +302,11 @@ func (t *winTray) addOrUpdateMenuItem(menuItemId uint32, parentId uint32, title
}
func (t *winTray) addSeparatorMenuItem(menuItemId, parentId uint32) error {
mi := menuItemInfo{
Mask: MIIM_FTYPE | MIIM_ID | MIIM_STATE,
Type: MFT_SEPARATOR,
ID: menuItemId,
ID: uint32(menuItemId),
}
mi.Size = uint32(unsafe.Sizeof(mi))
@ -416,7 +416,7 @@ 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
}
}
@ -426,6 +426,7 @@ func iconBytesToFilePath(iconBytes []byte) (string, error) {
// Loads an image from file and shows it in tray.
// Shell_NotifyIcon: https://msdn.microsoft.com/en-us/library/windows/desktop/bb762159(v=vs.85).aspx
func (t *winTray) setIcon(src string) error {
h, err := t.loadIconFrom(src)
if err != nil {
return err
@ -434,12 +435,7 @@ 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()
@ -448,6 +444,7 @@ func (t *winTray) setIcon(src string) error {
// Loads an image from file to be shown in tray or menu item.
// LoadImage: https://msdn.microsoft.com/en-us/library/windows/desktop/ms648045(v=vs.85).aspx
func (t *winTray) loadIconFrom(src string) (windows.Handle, error) {
// Save and reuse handles of loaded images
t.muLoadedImages.RLock()
h, ok := t.loadedImages[src]

View File

@ -61,7 +61,6 @@ const (
MIIM_SUBMENU = 0x00000004
MIM_APPLYTOSUBMENUS = 0x80000000
NIF_ICON = 0x00000002
NIF_TIP = 0x00000004
NIF_INFO = 0x00000010
NIF_MESSAGE = 0x00000001
SW_HIDE = 0

View File

@ -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)

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@ -2,7 +2,6 @@ package cmd
import (
"archive/zip"
"bufio"
"bytes"
"context"
"crypto/ed25519"
@ -21,9 +20,7 @@ import (
"path/filepath"
"regexp"
"runtime"
"strconv"
"strings"
"sync/atomic"
"syscall"
"time"
@ -32,6 +29,7 @@ import (
"github.com/olekukonko/tablewriter"
"github.com/spf13/cobra"
"golang.org/x/crypto/ssh"
"golang.org/x/exp/slices"
"golang.org/x/term"
"github.com/ollama/ollama/api"
@ -46,58 +44,28 @@ import (
"github.com/ollama/ollama/version"
)
var (
errModelNotFound = errors.New("no Modelfile or safetensors files found")
errModelfileNotFound = errors.New("specified Modelfile wasn't found")
)
func getModelfileName(cmd *cobra.Command) (string, error) {
fn, _ := cmd.Flags().GetString("file")
filename := fn
if filename == "" {
filename = "Modelfile"
}
absName, err := filepath.Abs(filename)
if err != nil {
return "", err
}
_, err = os.Stat(absName)
if err != nil {
return fn, err
}
return absName, nil
}
func CreateHandler(cmd *cobra.Command, args []string) error {
filename, _ := cmd.Flags().GetString("file")
filename, err := filepath.Abs(filename)
if err != nil {
return err
}
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
p := progress.NewProgress(os.Stderr)
defer p.Stop()
var reader io.Reader
filename, err := getModelfileName(cmd)
if os.IsNotExist(err) {
if filename == "" {
reader = strings.NewReader("FROM .\n")
} else {
return errModelfileNotFound
}
} else if err != nil {
f, err := os.Open(filename)
if err != nil {
return err
} else {
f, err := os.Open(filename)
if err != nil {
return err
}
reader = f
defer f.Close()
}
defer f.Close()
modelfile, err := parser.ParseFile(reader)
modelfile, err := parser.ParseFile(f)
if err != nil {
return err
}
@ -110,12 +78,6 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
status := "transferring model data"
spinner := progress.NewSpinner(status)
p.Add(status, spinner)
defer p.Stop()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
for i := range modelfile.Commands {
switch modelfile.Commands[i].Name {
@ -150,7 +112,7 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
path = tempfile
}
digest, err := createBlob(cmd, client, path, spinner)
digest, err := createBlob(cmd, client, path)
if err != nil {
return err
}
@ -200,6 +162,9 @@ func tempZipFiles(path string) (string, error) {
}
defer tempfile.Close()
zipfile := zip.NewWriter(tempfile)
defer zipfile.Close()
detectContentType := func(path string) (string, error) {
f, err := os.Open(path)
if err != nil {
@ -240,12 +205,6 @@ func tempZipFiles(path string) (string, error) {
// safetensors files might be unresolved git lfs references; skip if they are
// covers model-x-of-y.safetensors, model.fp32-x-of-y.safetensors, model.safetensors
files = append(files, st...)
} else if st, _ := glob(filepath.Join(path, "adapters.safetensors"), "application/octet-stream"); len(st) > 0 {
// covers adapters.safetensors
files = append(files, st...)
} else if st, _ := glob(filepath.Join(path, "adapter_model.safetensors"), "application/octet-stream"); len(st) > 0 {
// covers adapter_model.safetensors
files = append(files, st...)
} else if pt, _ := glob(filepath.Join(path, "pytorch_model*.bin"), "application/zip"); len(pt) > 0 {
// pytorch files might also be unresolved git lfs references; skip if they are
// covers pytorch_model-x-of-y.bin, pytorch_model.fp32-x-of-y.bin, pytorch_model.bin
@ -255,7 +214,7 @@ func tempZipFiles(path string) (string, error) {
// covers consolidated.x.pth, consolidated.pth
files = append(files, pt...)
} else {
return "", errModelNotFound
return "", errors.New("no safetensors or torch files found")
}
// add configuration files, json files are detected as text/plain
@ -265,14 +224,6 @@ func tempZipFiles(path string) (string, error) {
}
files = append(files, js...)
// bert models require a nested config.json
// TODO(mxyng): merge this with the glob above
js, err = glob(filepath.Join(path, "**/*.json"), "text/plain")
if err != nil {
return "", err
}
files = append(files, js...)
if tks, _ := glob(filepath.Join(path, "tokenizer.model"), "application/octet-stream"); len(tks) > 0 {
// add tokenizer.model if it exists, tokenizer.json is automatically picked up by the previous glob
// tokenizer.model might be a unresolved git lfs reference; error if it is
@ -282,9 +233,6 @@ func tempZipFiles(path string) (string, error) {
files = append(files, tks...)
}
zipfile := zip.NewWriter(tempfile)
defer zipfile.Close()
for _, file := range files {
f, err := os.Open(file)
if err != nil {
@ -302,11 +250,6 @@ func tempZipFiles(path string) (string, error) {
return "", err
}
zfi.Name, err = filepath.Rel(path, file)
if err != nil {
return "", err
}
zf, err := zipfile.CreateHeader(zfi)
if err != nil {
return "", err
@ -320,20 +263,13 @@ func tempZipFiles(path string) (string, error) {
return tempfile.Name(), nil
}
func createBlob(cmd *cobra.Command, client *api.Client, path string, spinner *progress.Spinner) (string, error) {
func createBlob(cmd *cobra.Command, client *api.Client, path string) (string, error) {
bin, err := os.Open(path)
if err != nil {
return "", err
}
defer bin.Close()
// Get file info to retrieve the size
fileInfo, err := bin.Stat()
if err != nil {
return "", err
}
fileSize := fileInfo.Size()
hash := sha256.New()
if _, err := io.Copy(hash, bin); err != nil {
return "", err
@ -343,83 +279,46 @@ func createBlob(cmd *cobra.Command, client *api.Client, path string, spinner *pr
return "", err
}
var pw progressWriter
status := "transferring model data 0%"
spinner.SetMessage(status)
done := make(chan struct{})
defer close(done)
go func() {
ticker := time.NewTicker(60 * time.Millisecond)
defer ticker.Stop()
for {
select {
case <-ticker.C:
spinner.SetMessage(fmt.Sprintf("transferring model data %d%%", int(100*pw.n.Load()/fileSize)))
case <-done:
spinner.SetMessage("transferring model data 100%")
return
}
}
}()
digest := fmt.Sprintf("sha256:%x", hash.Sum(nil))
if err = client.CreateBlob(cmd.Context(), digest, io.TeeReader(bin, &pw)); err != nil {
if err = client.CreateBlob(cmd.Context(), digest, bin); err != nil {
return "", err
}
return digest, nil
}
type progressWriter struct {
n atomic.Int64
}
func (w *progressWriter) Write(p []byte) (n int, err error) {
w.n.Add(int64(len(p)))
return len(p), nil
}
func loadOrUnloadModel(cmd *cobra.Command, opts *runOptions) error {
p := progress.NewProgress(os.Stderr)
defer p.StopAndClear()
spinner := progress.NewSpinner("")
p.Add("", spinner)
func RunHandler(cmd *cobra.Command, args []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
req := &api.GenerateRequest{
Model: opts.Model,
KeepAlive: opts.KeepAlive,
}
name := args[0]
return client.Generate(cmd.Context(), req, func(api.GenerateResponse) error { return nil })
}
func StopHandler(cmd *cobra.Command, args []string) error {
opts := &runOptions{
Model: args[0],
KeepAlive: &api.Duration{Duration: 0},
}
if err := loadOrUnloadModel(cmd, opts); err != nil {
if strings.Contains(err.Error(), "not found") {
return fmt.Errorf("couldn't find model \"%s\" to stop", args[0])
// check if the model exists on the server
show, err := client.Show(cmd.Context(), &api.ShowRequest{Name: name})
var statusError api.StatusError
switch {
case errors.As(err, &statusError) && statusError.StatusCode == http.StatusNotFound:
if err := PullHandler(cmd, []string{name}); err != nil {
return err
}
}
return nil
}
func RunHandler(cmd *cobra.Command, args []string) error {
show, err = client.Show(cmd.Context(), &api.ShowRequest{Name: name})
if err != nil {
return err
}
case err != nil:
return err
}
interactive := true
opts := runOptions{
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
Model: args[0],
WordWrap: os.Getenv("TERM") == "xterm-256color",
Options: map[string]interface{}{},
MultiModal: slices.Contains(show.Details.Families, "clip"),
ParentModel: show.Details.ParentModel,
}
format, err := cmd.Flags().GetString("format")
@ -463,53 +362,11 @@ func RunHandler(cmd *cobra.Command, args []string) error {
}
opts.WordWrap = !nowrap
// Fill out the rest of the options based on information about the
// model.
client, err := api.ClientFromEnvironment()
if err != nil {
return err
if !interactive {
return generate(cmd, opts)
}
name := args[0]
info, err := func() (*api.ShowResponse, error) {
showReq := &api.ShowRequest{Name: name}
info, err := client.Show(cmd.Context(), showReq)
var se api.StatusError
if errors.As(err, &se) && se.StatusCode == http.StatusNotFound {
if err := PullHandler(cmd, []string{name}); err != nil {
return nil, err
}
return client.Show(cmd.Context(), &api.ShowRequest{Name: name})
}
return info, err
}()
if err != nil {
return err
}
opts.MultiModal = len(info.ProjectorInfo) != 0
opts.ParentModel = info.Details.ParentModel
if interactive {
if err := loadOrUnloadModel(cmd, &opts); err != nil {
return err
}
for _, msg := range info.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 generateInteractive(cmd, opts)
}
return generate(cmd, opts)
return generateInteractive(cmd, opts)
}
func errFromUnknownKey(unknownKeyErr error) error {
@ -647,7 +504,7 @@ func ListHandler(cmd *cobra.Command, args []string) error {
table.SetHeaderLine(false)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding(" ")
table.SetTablePadding("\t")
table.AppendBulk(data)
table.Render()
@ -682,15 +539,7 @@ func ListRunningHandler(cmd *cobra.Command, args []string) error {
cpuPercent := math.Round(float64(sizeCPU) / float64(m.Size) * 100)
procStr = fmt.Sprintf("%d%%/%d%% CPU/GPU", int(cpuPercent), int(100-cpuPercent))
}
var until string
delta := time.Since(m.ExpiresAt)
if delta > 0 {
until = "Stopping..."
} else {
until = format.HumanTime(m.ExpiresAt, "Never")
}
data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), procStr, until})
data = append(data, []string{m.Name, m.Digest[:12], format.HumanBytes(m.Size), procStr, format.HumanTime(m.ExpiresAt, "Never")})
}
}
@ -701,7 +550,7 @@ func ListRunningHandler(cmd *cobra.Command, args []string) error {
table.SetHeaderLine(false)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding(" ")
table.SetTablePadding("\t")
table.AppendBulk(data)
table.Render()
@ -714,17 +563,6 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
return err
}
// Unload the model if it's running before deletion
opts := &runOptions{
Model: args[0],
KeepAlive: &api.Duration{Duration: 0},
}
if err := loadOrUnloadModel(cmd, opts); err != nil {
if !strings.Contains(err.Error(), "not found") {
return fmt.Errorf("unable to stop existing running model \"%s\": %s", args[0], err)
}
}
for _, name := range args {
req := api.DeleteRequest{Name: name}
if err := client.Delete(cmd.Context(), &req); err != nil {
@ -741,6 +579,10 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return err
}
if len(args) != 1 {
return errors.New("missing model name")
}
license, errLicense := cmd.Flags().GetBool("license")
modelfile, errModelfile := cmd.Flags().GetBool("modelfile")
parameters, errParams := cmd.Flags().GetBool("parameters")
@ -783,6 +625,8 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
if flagsSet > 1 {
return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
} else if flagsSet == 0 {
return errors.New("one of '--license', '--modelfile', '--parameters', '--system', or '--template' must be specified")
}
req := api.ShowRequest{Name: args[0]}
@ -791,103 +635,17 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return err
}
if flagsSet == 1 {
switch showType {
case "license":
fmt.Println(resp.License)
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
case "system":
fmt.Print(resp.System)
case "template":
fmt.Print(resp.Template)
}
return nil
}
return showInfo(resp, os.Stdout)
}
func showInfo(resp *api.ShowResponse, w io.Writer) error {
tableRender := func(header string, rows func() [][]string) {
fmt.Fprintln(w, " ", header)
table := tablewriter.NewWriter(w)
table.SetAlignment(tablewriter.ALIGN_LEFT)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding(" ")
switch header {
case "Template", "System", "License":
table.SetColWidth(100)
}
table.AppendBulk(rows())
table.Render()
fmt.Fprintln(w)
}
tableRender("Model", func() (rows [][]string) {
if resp.ModelInfo != nil {
arch := resp.ModelInfo["general.architecture"].(string)
rows = append(rows, []string{"", "architecture", arch})
rows = append(rows, []string{"", "parameters", format.HumanNumber(uint64(resp.ModelInfo["general.parameter_count"].(float64)))})
rows = append(rows, []string{"", "context length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.context_length", arch)].(float64), 'f', -1, 64)})
rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(resp.ModelInfo[fmt.Sprintf("%s.embedding_length", arch)].(float64), 'f', -1, 64)})
} else {
rows = append(rows, []string{"", "architecture", resp.Details.Family})
rows = append(rows, []string{"", "parameters", resp.Details.ParameterSize})
}
rows = append(rows, []string{"", "quantization", resp.Details.QuantizationLevel})
return
})
if resp.ProjectorInfo != nil {
tableRender("Projector", func() (rows [][]string) {
arch := resp.ProjectorInfo["general.architecture"].(string)
rows = append(rows, []string{"", "architecture", arch})
rows = append(rows, []string{"", "parameters", format.HumanNumber(uint64(resp.ProjectorInfo["general.parameter_count"].(float64)))})
rows = append(rows, []string{"", "embedding length", strconv.FormatFloat(resp.ProjectorInfo[fmt.Sprintf("%s.vision.embedding_length", arch)].(float64), 'f', -1, 64)})
rows = append(rows, []string{"", "dimensions", strconv.FormatFloat(resp.ProjectorInfo[fmt.Sprintf("%s.vision.projection_dim", arch)].(float64), 'f', -1, 64)})
return
})
}
if resp.Parameters != "" {
tableRender("Parameters", func() (rows [][]string) {
scanner := bufio.NewScanner(strings.NewReader(resp.Parameters))
for scanner.Scan() {
if text := scanner.Text(); text != "" {
rows = append(rows, append([]string{""}, strings.Fields(text)...))
}
}
return
})
}
head := func(s string, n int) (rows [][]string) {
scanner := bufio.NewScanner(strings.NewReader(s))
for scanner.Scan() && (len(rows) < n || n < 0) {
if text := scanner.Text(); text != "" {
rows = append(rows, []string{"", strings.TrimSpace(text)})
}
}
return
}
if resp.System != "" {
tableRender("System", func() [][]string {
return head(resp.System, 2)
})
}
if resp.License != "" {
tableRender("License", func() [][]string {
return head(resp.License, 2)
})
switch showType {
case "license":
fmt.Println(resp.License)
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
case "system":
fmt.Println(resp.System)
case "template":
fmt.Println(resp.Template)
}
return nil
@ -971,6 +729,7 @@ type runOptions struct {
WordWrap bool
Format string
System string
Template string
Images []api.ImageData
Options map[string]interface{}
MultiModal bool
@ -987,6 +746,7 @@ func displayResponse(content string, wordWrap bool, state *displayResponseState)
if wordWrap && termWidth >= 10 {
for _, ch := range content {
if state.lineLength+1 > termWidth-5 {
if runewidth.StringWidth(state.wordBuffer) > termWidth-10 {
fmt.Printf("%s%c", state.wordBuffer, ch)
state.wordBuffer = ""
@ -1164,6 +924,7 @@ func generate(cmd *cobra.Command, opts runOptions) error {
Images: opts.Images,
Format: opts.Format,
System: opts.System,
Template: opts.Template,
Options: opts.Options,
KeepAlive: opts.KeepAlive,
}
@ -1199,12 +960,18 @@ func generate(cmd *cobra.Command, opts runOptions) error {
return nil
}
func RunServer(_ *cobra.Command, _ []string) error {
func RunServer(cmd *cobra.Command, _ []string) error {
// retrieve the OLLAMA_HOST environment variable
ollamaHost, err := api.GetOllamaHost()
if err != nil {
return err
}
if err := initializeKeypair(); err != nil {
return err
}
ln, err := net.Listen("tcp", envconfig.Host().Host)
ln, err := net.Listen("tcp", net.JoinHostPort(ollamaHost.Host, ollamaHost.Port))
if err != nil {
return err
}
@ -1263,6 +1030,24 @@ func initializeKeypair() error {
return nil
}
//nolint:unused
func waitForServer(ctx context.Context, client *api.Client) error {
// wait for the server to start
timeout := time.After(5 * time.Second)
tick := time.Tick(500 * time.Millisecond)
for {
select {
case <-timeout:
return errors.New("timed out waiting for server to start")
case <-tick:
if err := client.Heartbeat(ctx); err == nil {
return nil // server has started
}
}
}
}
func checkServerHeartbeat(cmd *cobra.Command, _ []string) error {
client, err := api.ClientFromEnvironment()
if err != nil {
@ -1273,7 +1058,7 @@ func checkServerHeartbeat(cmd *cobra.Command, _ []string) error {
return err
}
if err := startApp(cmd.Context(), client); err != nil {
return errors.New("could not connect to ollama app, is it running?")
return fmt.Errorf("could not connect to ollama app, is it running?")
}
}
return nil
@ -1318,7 +1103,7 @@ func NewCLI() *cobra.Command {
log.SetFlags(log.LstdFlags | log.Lshortfile)
cobra.EnableCommandSorting = false
if runtime.GOOS == "windows" && term.IsTerminal(int(os.Stdout.Fd())) {
if runtime.GOOS == "windows" {
console.ConsoleFromFile(os.Stdin) //nolint:errcheck
}
@ -1350,7 +1135,7 @@ func NewCLI() *cobra.Command {
RunE: CreateHandler,
}
createCmd.Flags().StringP("file", "f", "", "Name of the Modelfile (default \"Modelfile\"")
createCmd.Flags().StringP("file", "f", "Modelfile", "Name of the Modelfile")
createCmd.Flags().StringP("quantize", "q", "", "Quantize model to this level (e.g. q4_0)")
showCmd := &cobra.Command{
@ -1380,15 +1165,6 @@ func NewCLI() *cobra.Command {
runCmd.Flags().Bool("insecure", false, "Use an insecure registry")
runCmd.Flags().Bool("nowordwrap", false, "Don't wrap words to the next line automatically")
runCmd.Flags().String("format", "", "Response format (e.g. json)")
stopCmd := &cobra.Command{
Use: "stop MODEL",
Short: "Stop a running model",
Args: cobra.ExactArgs(1),
PreRunE: checkServerHeartbeat,
RunE: StopHandler,
}
serveCmd := &cobra.Command{
Use: "serve",
Aliases: []string{"start"},
@ -1456,7 +1232,6 @@ func NewCLI() *cobra.Command {
createCmd,
showCmd,
runCmd,
stopCmd,
pullCmd,
pushCmd,
listCmd,
@ -1479,12 +1254,10 @@ func NewCLI() *cobra.Command {
envVars["OLLAMA_NUM_PARALLEL"],
envVars["OLLAMA_NOPRUNE"],
envVars["OLLAMA_ORIGINS"],
envVars["OLLAMA_SCHED_SPREAD"],
envVars["OLLAMA_TMPDIR"],
envVars["OLLAMA_FLASH_ATTENTION"],
envVars["OLLAMA_LLM_LIBRARY"],
envVars["OLLAMA_GPU_OVERHEAD"],
envVars["OLLAMA_LOAD_TIMEOUT"],
envVars["OLLAMA_MAX_VRAM"],
})
default:
appendEnvDocs(cmd, envs)
@ -1496,7 +1269,6 @@ func NewCLI() *cobra.Command {
createCmd,
showCmd,
runCmd,
stopCmd,
pullCmd,
pushCmd,
listCmd,

View File

@ -1,371 +0,0 @@
package cmd
import (
"bytes"
"context"
"encoding/json"
"net/http"
"net/http/httptest"
"os"
"path/filepath"
"strings"
"testing"
"github.com/google/go-cmp/cmp"
"github.com/spf13/cobra"
"github.com/ollama/ollama/api"
)
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",
},
}, &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",
},
}, &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("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`,
}, &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),
},
}, &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!
`,
}, &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, err := os.ReadFile(filepath.Join("..", "LICENSE"))
if err != nil {
t.Fatal(err)
}
if err := showInfo(&api.ShowResponse{
Details: api.ModelDetails{
Family: "test",
ParameterSize: "7B",
QuantizationLevel: "FP16",
},
License: string(license),
}, &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)
}
})
}
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: "crazyfile",
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 {
if tt.modelfileName != "" {
expectedFilename = tt.modelfileName
err := cmd.Flags().Set("file", tt.modelfileName)
if err != nil {
t.Fatalf("couldn't set file flag: %v", err)
}
}
}
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)
}
}
})
}
}

View File

@ -1,7 +1,6 @@
package cmd
import (
"cmp"
"errors"
"fmt"
"io"
@ -9,15 +8,15 @@ import (
"os"
"path/filepath"
"regexp"
"slices"
"sort"
"strings"
"github.com/spf13/cobra"
"golang.org/x/exp/maps"
"golang.org/x/exp/slices"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/progress"
"github.com/ollama/ollama/readline"
"github.com/ollama/ollama/types/errtypes"
)
@ -28,9 +27,74 @@ const (
MultilineNone MultilineState = iota
MultilinePrompt
MultilineSystem
MultilineTemplate
)
func loadModel(cmd *cobra.Command, opts *runOptions) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
p := progress.NewProgress(os.Stderr)
defer p.StopAndClear()
spinner := progress.NewSpinner("")
p.Add("", spinner)
showReq := api.ShowRequest{Name: opts.Model}
showResp, err := client.Show(cmd.Context(), &showReq)
if err != nil {
return err
}
opts.MultiModal = slices.Contains(showResp.Details.Families, "clip")
opts.ParentModel = showResp.Details.ParentModel
if len(showResp.Messages) > 0 {
opts.Messages = append(opts.Messages, showResp.Messages...)
}
chatReq := &api.ChatRequest{
Model: opts.Model,
Messages: []api.Message{},
}
if opts.KeepAlive != nil {
chatReq.KeepAlive = opts.KeepAlive
}
err = client.Chat(cmd.Context(), chatReq, func(resp api.ChatResponse) error {
p.StopAndClear()
if len(opts.Messages) > 0 {
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
})
if err != nil {
return err
}
return nil
}
func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.Messages = make([]api.Message, 0)
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")
@ -55,6 +119,7 @@ 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")
@ -100,7 +165,6 @@ 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")
@ -120,7 +184,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
return err
}
if envconfig.NoHistory() {
if envconfig.NoHistory {
scanner.HistoryDisable()
}
@ -165,6 +229,10 @@ 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
@ -196,7 +264,7 @@ 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 err := loadModel(cmd, &opts); err != nil {
return err
}
continue
@ -283,13 +351,17 @@ 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, `"""`)
@ -309,17 +381,23 @@ 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()
sb.Reset()
continue
@ -338,9 +416,10 @@ 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 {
@ -350,7 +429,15 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
switch args[1] {
case "info":
_ = showInfo(resp, os.Stderr)
fmt.Println("Model details:")
if len(resp.Details.Families) > 0 {
fmt.Printf("Family %s\n", strings.Join(resp.Details.Families, ", "))
} else if resp.Details.Family != "" {
fmt.Printf("Family %s\n", resp.Details.Family)
}
fmt.Printf("Parameter Size %s\n", resp.Details.ParameterSize)
fmt.Printf("Quantization Level %s\n", resp.Details.QuantizationLevel)
fmt.Println("")
case "license":
if resp.License == "" {
fmt.Println("No license was specified for this model.")
@ -383,9 +470,12 @@ 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:
@ -442,6 +532,13 @@ 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
}
@ -462,54 +559,60 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
}
func buildModelfile(opts runOptions) string {
var f parser.File
f.Commands = append(f.Commands, parser.Command{Name: "model", Args: cmp.Or(opts.ParentModel, opts.Model)})
var mf strings.Builder
model := opts.ParentModel
if model == "" {
model = opts.Model
}
fmt.Fprintf(&mf, "FROM %s\n", model)
if opts.System != "" {
f.Commands = append(f.Commands, parser.Command{Name: "system", Args: opts.System})
fmt.Fprintf(&mf, "SYSTEM \"\"\"%s\"\"\"\n", opts.System)
}
keys := maps.Keys(opts.Options)
slices.Sort(keys)
if opts.Template != "" {
fmt.Fprintf(&mf, "TEMPLATE \"\"\"%s\"\"\"\n", opts.Template)
}
keys := make([]string, 0)
for k := range opts.Options {
keys = append(keys, k)
}
sort.Strings(keys)
for _, k := range keys {
v := opts.Options[k]
var cmds []parser.Command
switch t := v.(type) {
case []string:
for _, s := range t {
cmds = append(cmds, parser.Command{Name: k, Args: s})
}
default:
cmds = append(cmds, parser.Command{Name: k, Args: fmt.Sprintf("%v", t)})
}
f.Commands = append(f.Commands, cmds...)
fmt.Fprintf(&mf, "PARAMETER %s %v\n", k, opts.Options[k])
}
fmt.Fprintln(&mf)
for _, msg := range opts.Messages {
f.Commands = append(f.Commands, parser.Command{Name: "message", Args: fmt.Sprintf("%s: %s", msg.Role, msg.Content)})
fmt.Fprintf(&mf, "MESSAGE %s \"\"\"%s\"\"\"\n", msg.Role, msg.Content)
}
return f.String()
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 {
@ -529,9 +632,10 @@ 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
}
@ -539,7 +643,7 @@ 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) {
@ -569,7 +673,7 @@ 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())

View File

@ -1,9 +1,10 @@
package cmd
import (
"bytes"
"testing"
"text/template"
"github.com/google/go-cmp/cmp"
"github.com/stretchr/testify/assert"
"github.com/ollama/ollama/api"
@ -55,53 +56,61 @@ d:\path with\spaces\seven.svg inbetween7 c:\users\jdoe\eight.png inbetween8
func TestModelfileBuilder(t *testing.T) {
opts := runOptions{
Model: "hork",
System: "You are part horse and part shark, but all hork. Do horklike things",
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]any{
"temperature": 0.9,
"seed": 42,
"penalize_newline": false,
"stop": []string{"hi", "there"},
},
Options: map[string]interface{}{},
}
t.Run("model", func(t *testing.T) {
expect := `FROM hork
SYSTEM You are part horse and part shark, but all hork. Do horklike things
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
PARAMETER stop there
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.
MESSAGE user """Hey there hork!"""
MESSAGE assistant """Yes it is true, I am half horse, half shark."""
`
actual := buildModelfile(opts)
if diff := cmp.Diff(expect, actual); diff != "" {
t.Errorf("mismatch (-want +got):\n%s", diff)
}
})
tmpl, err := template.New("").Parse(expectedModelfile)
assert.Nil(t, err)
t.Run("parent model", func(t *testing.T) {
opts.ParentModel = "horseshark"
expect := `FROM horseshark
SYSTEM You are part horse and part shark, but all hork. Do horklike things
var buf bytes.Buffer
err = tmpl.Execute(&buf, opts)
assert.Nil(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
PARAMETER stop there
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.
MESSAGE user """Hey there hork!"""
MESSAGE assistant """Yes it is true, I am half horse, half shark."""
`
actual := buildModelfile(opts)
if diff := cmp.Diff(expect, actual); diff != "" {
t.Errorf("mismatch (-want +got):\n%s", diff)
}
})
tmpl, err = template.New("").Parse(expectedModelfile)
assert.Nil(t, err)
var parentBuf bytes.Buffer
err = tmpl.Execute(&parentBuf, opts)
assert.Nil(t, err)
assert.Equal(t, parentBuf.String(), mf)
}

View File

@ -1,27 +0,0 @@
//go:build darwin || windows
package cmd
import (
"context"
"errors"
"time"
"github.com/ollama/ollama/api"
)
func waitForServer(ctx context.Context, client *api.Client) error {
// wait for the server to start
timeout := time.After(5 * time.Second)
tick := time.Tick(500 * time.Millisecond)
for {
select {
case <-timeout:
return errors.New("timed out waiting for server to start")
case <-tick:
if err := client.Heartbeat(ctx); err == nil {
return nil // server has started
}
}
}
}

View File

@ -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 {

View File

@ -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")
}

View File

@ -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")
}
}
}

View File

@ -1,232 +1,200 @@
package convert
import (
"cmp"
"encoding/binary"
"encoding/json"
"errors"
"fmt"
"io"
"io/fs"
"log/slog"
"os"
"path/filepath"
"slices"
"strings"
"google.golang.org/protobuf/proto"
"github.com/ollama/ollama/convert/sentencepiece"
"github.com/ollama/ollama/llm"
)
type ModelParameters struct {
Architectures []string `json:"architectures"`
VocabSize uint32 `json:"vocab_size"`
const (
_ int32 = iota
tokenTypeNormal
tokenTypeUnknown
tokenTypeControl
tokenTypeUserDefined
tokenTypeUnused
tokenTypeByte
)
type Params struct {
Architectures []string `json:"architectures"`
VocabSize int `json:"vocab_size"`
HiddenSize int `json:"hidden_size"` // n_embd
HiddenLayers int `json:"num_hidden_layers"` // n_layer
ContextSize int `json:"max_position_embeddings"`
IntermediateSize int `json:"intermediate_size"`
AttentionHeads int `json:"num_attention_heads"` // n_head
KeyValHeads int `json:"num_key_value_heads"`
NormEPS float64 `json:"rms_norm_eps"`
BoSTokenID int `json:"bos_token_id"`
EoSTokenID int `json:"eos_token_id"`
HeadDimension int `json:"head_dim"`
PaddingTokenID int `json:"pad_token_id"`
RopeFrequencyBase float64 `json:"rope_theta"`
Experts int `json:"num_local_experts"`
ExpertsUsed int `json:"num_experts_per_tok"`
PreTokenizer string
ByteOrder
}
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"`
type ByteOrder interface {
binary.ByteOrder
binary.AppendByteOrder
}
func (ModelParameters) KV(t *Tokenizer) llm.KV {
kv := llm.KV{
"general.file_type": uint32(1),
"general.quantization_version": uint32(2),
"tokenizer.ggml.pre": t.Pre,
"tokenizer.ggml.model": t.Vocabulary.Model,
"tokenizer.ggml.tokens": t.Vocabulary.Tokens,
"tokenizer.ggml.scores": t.Vocabulary.Scores,
"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
}
for _, sv := range t.SpecialVocabulary {
kv[fmt.Sprintf("tokenizer.ggml.%s_token_id", sv.Key())] = uint32(sv.ID)
kv[fmt.Sprintf("tokenizer.ggml.add_%s_token", sv.Key())] = sv.AddToken
}
return kv
type ModelArch interface {
GetTensors() error
LoadVocab() error
WriteGGUF(io.WriteSeeker) error
}
func (p AdapterParameters) KV() llm.KV {
var alpha float32
if p.LoraParameters.Alpha == 0 {
alpha = float32(p.Alpha)
} else {
alpha = p.LoraParameters.Alpha
}
kv := llm.KV{
"adapter.lora.alpha": alpha,
"adapter.type": "lora",
"general.file_type": uint32(1),
"general.type": "adapter",
"general.version": "v0.2",
}
return kv
type ModelFormat interface {
GetLayerName(string) (string, error)
GetTensors(string, *Params) ([]llm.Tensor, error)
GetParams(string) (*Params, error)
GetModelArch(string, string, *Params) (ModelArch, error)
}
func (ModelParameters) specialTokenTypes() []string {
return []string{
"bos", "eos", "unk", "sep", "pad", "cls", "mask",
}
type ModelData struct {
Path string
Name string
Params *Params
Vocab *Vocab
Tensors []llm.Tensor
Format ModelFormat
}
func (ModelParameters) writeFile(ws io.WriteSeeker, kv llm.KV, ts []llm.Tensor) error {
return llm.WriteGGUF(ws, kv, ts)
}
func (AdapterParameters) writeFile(ws io.WriteSeeker, kv llm.KV, ts []llm.Tensor) error {
return llm.WriteGGUF(ws, kv, ts)
}
type ModelConverter interface {
// KV maps parameters to LLM key-values
KV(*Tokenizer) llm.KV
// Tensors maps input tensors to LLM tensors. Model specific modifications can be done here.
Tensors([]Tensor) []llm.Tensor
// Replacements returns a list of string pairs to replace in tensor names.
// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
Replacements() []string
// specialTokenTypes returns any special token types the model uses
specialTokenTypes() []string
// writeFile writes the model to the provided io.WriteSeeker
writeFile(io.WriteSeeker, llm.KV, []llm.Tensor) error
}
type moreParser interface {
parseMore(fs.FS) error
}
type AdapterConverter interface {
// KV maps parameters to LLM key-values
KV(llm.KV) llm.KV
// Tensors maps input tensors to LLM tensors. Adapter specific modifications can be done here.
Tensors([]Tensor) []llm.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, llm.KV, []llm.Tensor) error
}
func ConvertAdapter(fsys fs.FS, ws io.WriteSeeker, baseKV llm.KV) error {
bts, err := fs.ReadFile(fsys, "adapter_config.json")
func GetModelFormat(dirname string) (ModelFormat, error) {
files, err := filepath.Glob(filepath.Join(dirname, "*"))
if err != nil {
return err
return nil, 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))
}
// 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")
if err != nil {
return err
}
var p ModelParameters
if err := json.Unmarshal(bts, &p); err != nil {
return err
}
if len(p.Architectures) < 1 {
return errors.New("unknown architecture")
}
var conv ModelConverter
switch p.Architectures[0] {
case "LlamaForCausalLM", "MistralForCausalLM":
conv = &llamaModel{}
case "MixtralForCausalLM":
conv = &mixtralModel{}
case "GemmaForCausalLM":
conv = &gemmaModel{}
case "Gemma2ForCausalLM":
conv = &gemma2Model{}
case "Phi3ForCausalLM":
conv = &phi3Model{}
case "BertModel":
conv = &bertModel{}
default:
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
for _, fn := range files {
if strings.HasSuffix(fn, ".safetensors") {
return &SafetensorFormat{}, nil
} else if strings.HasSuffix(fn, ".bin") || strings.HasSuffix(fn, ".pth") {
slog.Debug("model is torch")
return &TorchFormat{}, nil
}
}
t, err := parseTokenizer(fsys, conv.specialTokenTypes())
if err != nil {
return err
}
vocabSize := int(p.VocabSize)
switch {
case vocabSize > len(t.Vocabulary.Tokens):
slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
for i := range vocabSize - len(t.Vocabulary.Tokens) {
t.Vocabulary.Tokens = append(t.Vocabulary.Tokens, fmt.Sprintf("[PAD%d]", i))
t.Vocabulary.Scores = append(t.Vocabulary.Scores, -1)
t.Vocabulary.Types = append(t.Vocabulary.Types, tokenTypeUserDefined)
}
case vocabSize < len(t.Vocabulary.Tokens):
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()...))
if err != nil {
return err
}
return conv.writeFile(ws, conv.KV(t), conv.Tensors(ts))
return nil, fmt.Errorf("couldn't determine model format")
}
// Details on gguf's tokenizer can be found at:
// https://github.com/ggerganov/ggml/blob/master/docs/gguf.md#tokenizer
type Vocab struct {
Tokens []string
Scores []float32
Types []int32
Merges []string
}
func LoadSentencePieceTokens(dirpath string, params *Params) (*Vocab, error) {
slog.Info(fmt.Sprintf("reading vocab from %s", filepath.Join(dirpath, "tokenizer.model")))
in, err := os.ReadFile(filepath.Join(dirpath, "tokenizer.model"))
if err != nil {
return nil, err
}
// To regenerate sentencepiece from the protobufs use:
// protoc -I=./ --go_out=./ sentencepiece_model.proto
modelProto := &sentencepiece.ModelProto{}
if err := proto.Unmarshal(in, modelProto); err != nil {
return nil, err
}
v := &Vocab{
Tokens: make([]string, 0),
Scores: make([]float32, 0),
Types: make([]int32, 0),
}
pieces := modelProto.GetPieces()
for _, p := range pieces {
v.Tokens = append(v.Tokens, p.GetPiece())
v.Scores = append(v.Scores, p.GetScore())
t := p.GetType()
switch t {
case sentencepiece.ModelProto_SentencePiece_UNKNOWN:
case sentencepiece.ModelProto_SentencePiece_CONTROL:
case sentencepiece.ModelProto_SentencePiece_UNUSED:
case sentencepiece.ModelProto_SentencePiece_BYTE:
default:
t = sentencepiece.ModelProto_SentencePiece_NORMAL
}
v.Types = append(v.Types, int32(t))
}
slog.Info(fmt.Sprintf("vocab size: %d", len(v.Tokens)))
// add any additional tokens
addIn, err := os.ReadFile(filepath.Join(dirpath, "added_tokens.json"))
if os.IsNotExist(err) {
return v, nil
} else if err != nil {
return nil, err
}
slog.Info("reading user defined tokens")
var extraTokenData map[string]int
if err := json.Unmarshal(addIn, &extraTokenData); err != nil {
return nil, err
}
type token struct {
key string
pos int
}
extraTokens := make([]token, 0)
for k, id := range extraTokenData {
extraTokens = append(extraTokens, token{k, id})
}
slices.SortFunc(extraTokens, func(a, b token) int {
return cmp.Compare(a.pos, b.pos)
})
numToks := len(v.Tokens)
for cnt, t := range extraTokens {
// the token id should match the specific index for the total number of tokens
if t.pos != cnt+numToks {
return nil, fmt.Errorf("token ID '%d' for '%s' doesn't match total token size", t.pos, t.key)
}
v.Tokens = append(v.Tokens, t.key)
v.Scores = append(v.Scores, -1000.0)
v.Types = append(v.Types, tokenTypeUserDefined)
}
slog.Info(fmt.Sprintf("vocab size w/ extra tokens: %d", len(v.Tokens)))
if params.VocabSize > len(v.Tokens) {
missingTokens := params.VocabSize - len(v.Tokens)
slog.Warn(fmt.Sprintf("vocab is missing %d tokens", missingTokens))
for cnt := 0; cnt < missingTokens; cnt++ {
v.Tokens = append(v.Tokens, fmt.Sprintf("<dummy%05d>", cnt+1))
v.Scores = append(v.Scores, -1)
v.Types = append(v.Types, tokenTypeUserDefined)
}
}
return v, nil
}

View File

@ -1,174 +0,0 @@
package convert
import (
"cmp"
"encoding/json"
"io/fs"
"path/filepath"
"slices"
"strings"
"github.com/ollama/ollama/llm"
)
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) llm.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) []llm.Tensor {
var out []llm.Tensor
for _, t := range ts {
if slices.Contains([]string{
"embeddings.position_ids",
"pooler.dense.weight",
"pooler.dense.bias",
}, t.Name()) {
continue
}
out = append(out, llm.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",
}
}

View File

@ -1,100 +0,0 @@
package convert
import (
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type gemmaModel 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"`
RMSNormEPS float32 `json:"rms_norm_eps"`
HeadDim uint32 `json:"head_dim"`
}
var _ ModelConverter = (*gemmaModel)(nil)
func (p *gemmaModel) KV(t *Tokenizer) llm.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "gemma"
kv["gemma.context_length"] = p.MaxPositionEmbeddings
kv["gemma.embedding_length"] = p.HiddenSize
kv["gemma.block_count"] = p.HiddenLayers
kv["gemma.feed_forward_length"] = p.IntermediateSize
kv["gemma.attention.head_count"] = p.NumAttentionHeads
kv["gemma.attention.head_count_kv"] = p.NumKeyValueHeads
kv["gemma.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
kv["gemma.attention.key_length"] = p.HeadDim
kv["gemma.attention.value_length"] = p.HeadDim
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 *gemmaModel) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
for _, t := range ts {
if strings.HasSuffix(t.Name(), "_norm.weight") {
t.SetRepacker(p.addOne)
}
out = append(out, llm.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),
WriterTo: t,
})
}
return out
}
func (p *gemmaModel) 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", "ffn_norm",
}
}
func (*gemmaModel) 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]))
n, err := n.Add(ones)
if err != nil {
return nil, err
}
ts, err := native.SelectF32(n, 0)
if err != nil {
return nil, err
}
var f32s []float32
for _, t := range ts {
f32s = append(f32s, t...)
}
return f32s, nil
}

View File

@ -1,53 +0,0 @@
package convert
import (
"github.com/ollama/ollama/llm"
)
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) llm.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",
}
}

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@ -1,91 +0,0 @@
package convert
import (
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type gemma2Adapter struct {
AdapterParameters
}
var _ AdapterConverter = (*gemma2Adapter)(nil)
func (p *gemma2Adapter) KV(baseKV llm.KV) llm.KV {
kv := p.AdapterParameters.KV()
kv["general.architecture"] = "gemma2"
return kv
}
func (p *gemma2Adapter) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.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, llm.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
}

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@ -1,213 +0,0 @@
package convert
import (
"cmp"
"fmt"
"math"
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type llamaModel 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"`
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
} `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)
func (p *llamaModel) KV(t *Tokenizer) llm.KV {
kv := p.ModelParameters.KV(t)
kv["general.architecture"] = "llama"
kv["llama.vocab_size"] = p.VocabSize
kv["llama.block_count"] = cmp.Or(p.NLayers, p.NumHiddenLayers, p.NLayer)
if contextLength := cmp.Or(p.MaxPositionEmbeddings, p.NCtx); contextLength > 0 {
kv["llama.context_length"] = contextLength
}
if embeddingLength := cmp.Or(p.HiddenSize, p.NEmbd); embeddingLength > 0 {
kv["llama.embedding_length"] = cmp.Or(p.HiddenSize, p.NEmbd)
}
if feedForwardLength := cmp.Or(p.IntermediateSize, p.NInner); feedForwardLength > 0 {
kv["llama.feed_forward_length"] = cmp.Or(p.IntermediateSize, p.NInner)
}
if headCount := cmp.Or(p.NumAttentionHeads, p.NHead); headCount > 0 {
kv["llama.attention.head_count"] = cmp.Or(p.NumAttentionHeads, p.NHead)
kv["llama.rope.dimension_count"] = p.HiddenSize / headCount
}
if p.RopeTheta > 0 {
kv["llama.rope.freq_base"] = p.RopeTheta
}
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 {
kv["llama.attention.head_count_kv"] = p.NumKeyValueHeads
}
if p.RMSNormEPS > 0 {
kv["llama.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
}
if layerNormEpsilon := cmp.Or(p.LayerNormEPS, p.LayerNormEpsilon, p.NormEpsilon); layerNormEpsilon > 0 {
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
}
return kv
}
func (p *llamaModel) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
if p.RopeScaling.factors != nil {
out = append(out, llm.Tensor{
Name: "rope_freqs.weight",
Kind: 0,
Shape: []uint64{uint64(len(p.RopeScaling.factors))},
WriterTo: p.RopeScaling.factors,
})
}
for _, t := range ts {
if strings.HasSuffix(t.Name(), "attn_q.weight") ||
strings.HasSuffix(t.Name(), "attn_k.weight") {
t.SetRepacker(p.repack)
}
out = append(out, llm.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),
WriterTo: t,
})
}
return out
}
func (p *llamaModel) 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.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", "ffn_norm",
}
}
func (p *llamaModel) 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.NumAttentionHeads
} else if strings.HasSuffix(name, "attn_k.weight") {
heads = cmp.Or(p.NumKeyValueHeads, p.NumAttentionHeads)
} else {
return nil, fmt.Errorf("unknown tensor for repack: %s", name)
}
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
}

View File

@ -1,169 +0,0 @@
package convert
import (
"cmp"
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
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 llm.KV) llm.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) []llm.Tensor {
var out []llm.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, llm.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
}

View File

@ -1,94 +0,0 @@
package convert
import (
"fmt"
"io"
"slices"
"strings"
"github.com/ollama/ollama/llm"
)
type mixtralModel struct {
llamaModel
NumLocalExperts uint32 `json:"num_local_experts"`
NumExpertsPerToken uint32 `json:"num_experts_per_tok"`
}
func (p *mixtralModel) KV(t *Tokenizer) llm.KV {
kv := p.llamaModel.KV(t)
if p.NumLocalExperts > 0 {
kv["llama.expert_count"] = p.NumLocalExperts
}
if p.NumExpertsPerToken > 0 {
kv["llama.expert_used_count"] = p.NumExpertsPerToken
}
return kv
}
func (p *mixtralModel) Tensors(ts []Tensor) []llm.Tensor {
oldnew := []string{
"model.layers", "blk",
"w1", "ffn_gate_exps",
"w2", "ffn_down_exps",
"w3", "ffn_up_exps",
}
for i := range p.NumLocalExperts {
oldnew = append(oldnew, fmt.Sprintf(".block_sparse_moe.experts.%d.", i), ".")
}
// group experts of the same layer (model.layers.%d) and type (w[123]) into a single tensor
namer := strings.NewReplacer(oldnew...)
experts := make(map[string]experts)
// merge experts into a single tensor while removing them from ts
ts = slices.DeleteFunc(ts, func(t Tensor) bool {
if !strings.Contains(t.Name(), ".block_sparse_moe.experts.") {
return false
}
name := namer.Replace(t.Name())
experts[name] = append(experts[name], t)
return true
})
var out []llm.Tensor
for n, e := range experts {
// TODO(mxyng): sanity check experts
out = append(out, llm.Tensor{
Name: n,
Kind: e[0].Kind(),
Shape: append([]uint64{uint64(len(e))}, e[0].Shape()...),
WriterTo: e,
})
}
return append(out, p.llamaModel.Tensors(ts)...)
}
func (p *mixtralModel) Replacements() []string {
return append(
p.llamaModel.Replacements(),
"block_sparse_moe.gate", "ffn_gate_inp",
)
}
type experts []Tensor
func (e experts) WriteTo(w io.Writer) (int64, error) {
// TODO(mxyng): experts _should_ be numerically sorted by expert but this should check
for _, t := range e {
// the canonical merged experts tensor stacks all experts along a new, 0 axis,
// e.g. `tensor.Stack(0, e[0], e[1:]...)`, which requires allocating temporary buffers
// this accomplishes the same thing by writing each expert tensor in sequence
if _, err := t.WriteTo(w); err != nil {
return 0, err
}
}
return 0, nil
}

View File

@ -1,123 +0,0 @@
package convert
import (
"cmp"
"encoding/binary"
"io"
"math"
"strings"
"sync"
"github.com/ollama/ollama/llm"
)
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) llm.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) []llm.Tensor {
var addRopeFactors sync.Once
out := make([]llm.Tensor, 0, len(ts)+2)
for _, t := range ts {
if strings.HasPrefix(t.Name(), "blk.0.") {
addRopeFactors.Do(func() {
out = append(out, llm.Tensor{
Name: "rope_factors_long.weight",
Kind: 0,
Shape: []uint64{uint64(len(p.RopeScaling.LongFactor))},
WriterTo: p.RopeScaling.LongFactor,
}, llm.Tensor{
Name: "rope_factors_short.weight",
Kind: 0,
Shape: []uint64{uint64(len(p.RopeScaling.ShortFactor))},
WriterTo: p.RopeScaling.ShortFactor,
})
})
}
out = append(out, llm.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
}

View File

@ -1,44 +1,48 @@
//go:build slow
package convert
import (
"bytes"
"crypto/sha256"
"encoding/binary"
"encoding/hex"
"encoding/json"
"flag"
"fmt"
"io"
"io/fs"
"log/slog"
"math"
"os"
"path/filepath"
"slices"
"strings"
"testing"
"golang.org/x/exp/maps"
"github.com/ollama/ollama/llm"
)
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, llm.KV, *llm.Tensors) {
func convertFull(t *testing.T, p string) (llm.KV, llm.Tensors) {
t.Helper()
mf, err := GetModelFormat(p)
if err != nil {
t.Fatal(err)
}
params, err := mf.GetParams(p)
if err != nil {
t.Fatal(err)
}
arch, err := mf.GetModelArch("", p, params)
if err != nil {
t.Fatal(err)
}
if err := arch.LoadVocab(); err != nil {
t.Fatal(err)
}
if err := arch.GetTensors(); err != nil {
t.Fatal(err)
}
f, err := os.CreateTemp(t.TempDir(), "f16")
if err != nil {
t.Fatal(err)
}
defer f.Close()
if err := ConvertModel(fsys, f); err != nil {
if err := arch.WriteGGUF(f); err != nil {
t.Fatal(err)
}
@ -46,431 +50,54 @@ func convertFull(t *testing.T, fsys fs.FS) (*os.File, llm.KV, *llm.Tensors) {
if err != nil {
t.Fatal(err)
}
t.Cleanup(func() { r.Close() })
defer r.Close()
m, _, err := llm.DecodeGGML(r, math.MaxInt)
m, _, err := llm.DecodeGGML(r)
if err != nil {
t.Fatal(err)
}
if _, err := r.Seek(0, io.SeekStart); err != nil {
t.Fatal(err)
}
return r, m.KV(), m.Tensors()
return m.KV(), m.Tensors()
}
func generateResultsJSON(t *testing.T, f *os.File, kv llm.KV, tensors *llm.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))
}
func TestConvertFull(t *testing.T) {
cases := []struct {
path string
arch string
tensors int
layers int
}{
{"Meta-Llama-3-8B-Instruct", "llama", 291, 35},
{"Mistral-7B-Instruct-v0.2", "llama", 291, 35},
{"Mixtral-8x7B-Instruct-v0.1", "llama", 291, 35},
{"gemma-2b-it", "gemma", 164, 20},
}
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")
flag.Parse()
slog.SetLogLoggerLevel(level)
os.Exit(m.Run())
}
func TestConvertModel(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",
}
for i := range cases {
tt := cases[i]
t.Run(tt, func(t *testing.T) {
t.Parallel()
p := filepath.Join("testdata", tt)
if testing.Short() {
t.Skip("skipping in short mode")
} else if _, err := os.Stat(p); err != nil {
for _, tt := range cases {
t.Run(tt.path, func(t *testing.T) {
p := filepath.Join("testdata", tt.path)
if _, err := os.Stat(p); err != nil {
t.Skipf("%s not found", p)
}
f, kv, tensors := convertFull(t, os.DirFS(p))
actual := generateResultsJSON(t, f, kv, tensors)
kv, tensors := convertFull(t, p)
expectFile, err := os.Open(filepath.Join("testdata", fmt.Sprintf("%s.json", tt)))
if err != nil {
t.Fatal(err)
if kv.Architecture() != tt.arch {
t.Fatalf("expected llama, got %s", kv.Architecture())
}
var expect map[string]string
if err := json.NewDecoder(expectFile).Decode(&expect); err != nil {
t.Fatal(err)
if kv.FileType().String() != "F16" {
t.Fatalf("expected F16, got %s", kv.FileType())
}
keys := maps.Keys(expect)
slices.Sort(keys)
for _, k := range keys {
if v, ok := actual[k]; !ok {
t.Errorf("missing %s", k)
} else if v != expect[k] {
t.Errorf("unexpected %s: want %s, got %s", k, expect[k], v)
}
if len(tensors) != tt.tensors {
t.Fatalf("expected %d tensors, got %d", tt.tensors, len(tensors))
}
layers := tensors.Layers()
if len(layers) != tt.layers {
t.Fatalf("expected %d layers, got %d", tt.layers, len(layers))
}
})
}
}
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)
}
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 := llm.DecodeGGML(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)
if err != nil {
t.Fatal(err)
}
}
ones = make([]float32, 1024*8)
for i := range ones {
ones[i] = float32(1)
}
err = binary.Write(&buf, binary.LittleEndian, ones)
if err != nil {
t.Fatal(err)
}
fdata, err := os.Create(filepath.Join(tempDir, "adapters.safetensors"))
if err != nil {
t.Fatal(err)
}
defer fdata.Close()
_, err = fdata.Write(buf.Bytes())
if err != nil {
t.Fatal(err)
}
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()
_, err = f.WriteString(configData)
if err != nil {
t.Fatal(err)
}
}

View File

@ -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)
}

103
convert/gemma.go Normal file
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@ -0,0 +1,103 @@
package convert
import (
"fmt"
"io"
"log/slog"
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type GemmaModel struct {
ModelData
}
func addOnes(data []float32, vectorSize int) ([]float32, error) {
n := tensor.New(tensor.WithShape(vectorSize), tensor.WithBacking(data))
ones := tensor.Ones(tensor.Float32, vectorSize)
n, err := n.Add(ones)
if err != nil {
return nil, err
}
ts, err := native.SelectF32(n, 0)
if err != nil {
return nil, err
}
var f32s []float32
for _, t := range ts {
f32s = append(f32s, t...)
}
return f32s, nil
}
func (m *GemmaModel) GetTensors() error {
t, err := m.Format.GetTensors(m.Path, m.Params)
if err != nil {
return err
}
slog.Debug(fmt.Sprintf("Total tensors: %d", len(t)))
for _, l := range t {
if strings.HasSuffix(l.Name, "norm.weight") {
wt := l.WriterTo.(safetensorWriterTo)
wt.repacker = m.Repack
l.WriterTo = wt
}
m.Tensors = append(m.Tensors, l)
}
return nil
}
func (m *GemmaModel) LoadVocab() error {
v, err := LoadSentencePieceTokens(m.Path, m.Params)
if err != nil {
return err
}
m.Vocab = v
return nil
}
func (m *GemmaModel) Repack(_ string, data []float32, shape []uint64) ([]float32, error) {
return addOnes(data, int(shape[0]))
}
func (m *GemmaModel) WriteGGUF(ws io.WriteSeeker) error {
kv := llm.KV{
"general.architecture": "gemma",
"general.name": m.Name,
"gemma.context_length": uint32(m.Params.ContextSize),
"gemma.embedding_length": uint32(m.Params.HiddenSize),
"gemma.block_count": uint32(m.Params.HiddenLayers),
"gemma.feed_forward_length": uint32(m.Params.IntermediateSize),
"gemma.attention.head_count": uint32(m.Params.AttentionHeads),
"gemma.attention.head_count_kv": uint32(m.Params.KeyValHeads),
"gemma.attention.layer_norm_rms_epsilon": float32(m.Params.NormEPS),
"gemma.attention.key_length": uint32(m.Params.HeadDimension),
"gemma.attention.value_length": uint32(m.Params.HeadDimension),
"general.file_type": uint32(1),
"tokenizer.ggml.model": "llama",
"tokenizer.ggml.tokens": m.Vocab.Tokens,
"tokenizer.ggml.scores": m.Vocab.Scores,
"tokenizer.ggml.token_type": m.Vocab.Types,
"tokenizer.ggml.bos_token_id": uint32(m.Params.BoSTokenID),
"tokenizer.ggml.eos_token_id": uint32(m.Params.EoSTokenID),
"tokenizer.ggml.padding_token_id": uint32(m.Params.PaddingTokenID),
"tokenizer.ggml.unknown_token_id": uint32(3),
"tokenizer.ggml.add_bos_token": true,
"tokenizer.ggml.add_eos_token": false,
}
return llm.NewGGUFV3(m.Params.ByteOrder).Encode(ws, kv, m.Tensors)
}

158
convert/llama.go Normal file
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@ -0,0 +1,158 @@
package convert
import (
"cmp"
"errors"
"fmt"
"io"
"os"
"path/filepath"
"regexp"
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type LlamaModel struct {
ModelData
}
func (m *LlamaModel) GetTensors() error {
t, err := m.Format.GetTensors(m.Path, m.Params)
if err != nil {
return err
}
pattern := `^blk\.[0-9]+\.attn_(?P<layer>q|k)\.weight$`
re, err := regexp.Compile(pattern)
if err != nil {
return err
}
for _, l := range t {
matches := re.FindAllStringSubmatch(l.Name, -1)
if len(matches) > 0 {
switch m.Format.(type) {
case *TorchFormat:
wt := l.WriterTo.(torchWriterTo)
wt.repacker = m.Repack
l.WriterTo = wt
case *SafetensorFormat:
wt := l.WriterTo.(safetensorWriterTo)
wt.repacker = m.Repack
l.WriterTo = wt
}
}
m.Tensors = append(m.Tensors, l)
}
return nil
}
func (m *LlamaModel) LoadVocab() (err error) {
pre, ts, merges, err := parseTokens(filepath.Join(m.Path, "tokenizer.json"))
if errors.Is(err, os.ErrNotExist) {
return nil
} else if err != nil {
return err
}
m.Vocab = &Vocab{}
for _, t := range ts {
m.Vocab.Tokens = append(m.Vocab.Tokens, t.Content)
m.Vocab.Types = append(m.Vocab.Types, t.Type())
}
m.Vocab.Merges = merges
m.Params.PreTokenizer = pre
return nil
}
func (m *LlamaModel) WriteGGUF(ws io.WriteSeeker) error {
kv := llm.KV{
"general.architecture": "llama",
"general.name": m.Name,
"llama.vocab_size": uint32(len(m.Vocab.Tokens)),
"llama.context_length": uint32(m.Params.ContextSize),
"llama.embedding_length": uint32(m.Params.HiddenSize),
"llama.block_count": uint32(m.Params.HiddenLayers),
"llama.feed_forward_length": uint32(m.Params.IntermediateSize),
"llama.rope.freq_base": float32(m.Params.RopeFrequencyBase),
"llama.rope.dimension_count": uint32(m.Params.HiddenSize / m.Params.AttentionHeads),
"llama.attention.head_count": uint32(m.Params.AttentionHeads),
"llama.attention.head_count_kv": uint32(m.Params.KeyValHeads),
"llama.attention.layer_norm_rms_epsilon": float32(m.Params.NormEPS),
"general.file_type": uint32(1),
"tokenizer.ggml.model": "gpt2",
"tokenizer.ggml.pre": m.Params.PreTokenizer,
"tokenizer.ggml.tokens": m.Vocab.Tokens,
"tokenizer.ggml.token_type": m.Vocab.Types,
"tokenizer.ggml.bos_token_id": uint32(m.Params.BoSTokenID),
"tokenizer.ggml.eos_token_id": uint32(m.Params.EoSTokenID),
"tokenizer.ggml.unknown_token_id": uint32(0),
}
if len(m.Vocab.Merges) > 0 {
kv["tokenizer.ggml.merges"] = m.Vocab.Merges
} else {
kv["tokenizer.ggml.scores"] = m.Vocab.Scores
}
return llm.NewGGUFV3(m.Params.ByteOrder).Encode(ws, kv, m.Tensors)
}
func (m *LlamaModel) Repack(name string, data []float32, shape []uint64) ([]float32, error) {
return llamaRepack(name, m.Params, data, shape)
}
func llamaRepack(name string, params *Params, data []float32, shape []uint64) ([]float32, error) {
var dims []int
for _, dim := range shape {
if dim != 0 {
dims = append(dims, int(dim))
}
}
var heads int
if strings.HasSuffix(name, "attn_q.weight") {
heads = params.AttentionHeads
} else if strings.HasSuffix(name, "attn_k.weight") {
heads = cmp.Or(params.KeyValHeads, params.AttentionHeads)
} else {
return nil, fmt.Errorf("unknown tensor name: %s", name)
}
n := tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
if err := n.Reshape(append([]int{heads, 2, dims[0] / 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
}

79
convert/mistral.go Normal file
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@ -0,0 +1,79 @@
package convert
import (
"io"
"regexp"
"github.com/ollama/ollama/llm"
)
type MistralModel struct {
ModelData
}
func (m *MistralModel) GetTensors() error {
t, err := m.Format.GetTensors(m.Path, m.Params)
if err != nil {
return err
}
pattern := `^blk\.[0-9]+\.attn_(?P<layer>q|k)\.weight$`
re, err := regexp.Compile(pattern)
if err != nil {
return err
}
for _, l := range t {
matches := re.FindAllStringSubmatch(l.Name, -1)
if len(matches) > 0 {
wt := l.WriterTo.(safetensorWriterTo)
wt.repacker = m.Repack
l.WriterTo = wt
}
m.Tensors = append(m.Tensors, l)
}
return nil
}
func (m *MistralModel) LoadVocab() error {
v, err := LoadSentencePieceTokens(m.Path, m.Params)
if err != nil {
return err
}
m.Vocab = v
return nil
}
func (m *MistralModel) WriteGGUF(ws io.WriteSeeker) error {
kv := llm.KV{
"general.architecture": "llama",
"general.name": m.Name,
"llama.context_length": uint32(m.Params.ContextSize),
"llama.embedding_length": uint32(m.Params.HiddenSize),
"llama.block_count": uint32(m.Params.HiddenLayers),
"llama.feed_forward_length": uint32(m.Params.IntermediateSize),
"llama.rope.dimension_count": uint32(m.Params.HiddenSize / m.Params.AttentionHeads),
"llama.attention.head_count": uint32(m.Params.AttentionHeads),
"llama.attention.head_count_kv": uint32(m.Params.KeyValHeads),
"llama.attention.layer_norm_rms_epsilon": float32(m.Params.NormEPS),
"general.file_type": uint32(1),
"tokenizer.ggml.model": "llama",
"tokenizer.ggml.tokens": m.Vocab.Tokens,
"tokenizer.ggml.scores": m.Vocab.Scores,
"tokenizer.ggml.token_type": m.Vocab.Types,
"tokenizer.ggml.bos_token_id": uint32(m.Params.BoSTokenID),
"tokenizer.ggml.eos_token_id": uint32(m.Params.EoSTokenID),
"tokenizer.ggml.add_bos_token": true,
"tokenizer.ggml.add_eos_token": false,
"tokenizer.ggml.unknown_token_id": uint32(0),
}
return llm.NewGGUFV3(m.Params.ByteOrder).Encode(ws, kv, m.Tensors)
}
func (m *MistralModel) Repack(name string, data []float32, shape []uint64) ([]float32, error) {
return llamaRepack(name, m.Params, data, shape)
}

87
convert/mixtral.go Normal file
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package convert
import (
"io"
"regexp"
"github.com/ollama/ollama/llm"
)
type MixtralModel struct {
ModelData
}
func (m *MixtralModel) GetTensors() error {
t, err := m.Format.GetTensors(m.Path, m.Params)
if err != nil {
return err
}
pattern := `^blk\.[0-9]+\.attn_(?P<layer>q|k)\.weight$`
re, err := regexp.Compile(pattern)
if err != nil {
return err
}
for _, l := range t {
matches := re.FindAllStringSubmatch(l.Name, -1)
if len(matches) > 0 {
wt := l.WriterTo.(safetensorWriterTo)
wt.repacker = m.Repack
l.WriterTo = wt
}
m.Tensors = append(m.Tensors, l)
}
return nil
}
func (m *MixtralModel) LoadVocab() error {
v, err := LoadSentencePieceTokens(m.Path, m.Params)
if err != nil {
return err
}
m.Vocab = v
return nil
}
func (m *MixtralModel) WriteGGUF(ws io.WriteSeeker) error {
kv := llm.KV{
"general.architecture": "llama",
"general.name": m.Name,
"llama.block_count": uint32(m.Params.HiddenLayers),
"llama.context_length": uint32(m.Params.ContextSize),
"llama.embedding_length": uint32(m.Params.HiddenSize),
"llama.feed_forward_length": uint32(m.Params.IntermediateSize),
"llama.attention.head_count": uint32(m.Params.AttentionHeads),
"llama.attention.head_count_kv": uint32(m.Params.KeyValHeads),
"llama.rope.freq_base": float32(m.Params.RopeFrequencyBase),
"llama.attention.layer_norm_rms_epsilon": float32(m.Params.NormEPS),
"llama.expert_count": uint32(m.Params.Experts),
"llama.expert_used_count": uint32(m.Params.ExpertsUsed),
"llama.vocab_size": uint32(len(m.Vocab.Tokens)),
"llama.rope.dimension_count": uint32(m.Params.HiddenSize / m.Params.AttentionHeads),
"general.file_type": uint32(1),
"tokenizer.ggml.model": "llama",
"tokenizer.ggml.tokens": m.Vocab.Tokens,
"tokenizer.ggml.scores": m.Vocab.Scores,
"tokenizer.ggml.token_type": m.Vocab.Types,
"tokenizer.ggml.bos_token_id": uint32(m.Params.BoSTokenID),
"tokenizer.ggml.eos_token_id": uint32(m.Params.EoSTokenID),
"tokenizer.ggml.unknown_token_id": uint32(0),
"tokenizer.ggml.add_bos_token": true,
"tokenizer.ggml.add_eos_token": false,
}
return llm.NewGGUFV3(m.Params.ByteOrder).Encode(ws, kv, m.Tensors)
}
func (m *MixtralModel) Repack(name string, data []float32, shape []uint64) ([]float32, error) {
return llamaRepack(name, m.Params, data, shape)
}

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@ -1,86 +0,0 @@
package convert
import (
"errors"
"io"
"io/fs"
"strings"
)
type Tensor interface {
Name() string
Shape() []uint64
Kind() uint32
SetRepacker(repacker)
WriteTo(io.Writer) (int64, error)
}
type tensorBase struct {
name string
shape []uint64
repacker
}
func (t tensorBase) Name() string {
return t.name
}
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
return 0
}
switch len(t.shape) {
case 0:
panic("invalid tensor shape")
case 1:
return tensorKindF32
default:
return tensorKindF16
}
}
func (t *tensorBase) SetRepacker(fn repacker) {
t.repacker = fn
}
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)
}{
{"model-*-of-*.safetensors", parseSafetensors},
{"model.safetensors", parseSafetensors},
{"adapters.safetensors", parseSafetensors},
{"adapter_model.safetensors", parseSafetensors},
{"pytorch_model-*-of-*.bin", parseTorch},
{"pytorch_model.bin", parseTorch},
{"consolidated.*.pth", parseTorch},
}
for _, pattern := range patterns {
matches, err := fs.Glob(fsys, pattern.Pattern)
if err != nil {
return nil, err
}
if len(matches) > 0 {
return pattern.Func(fsys, replacer, matches...)
}
}
return nil, errors.New("unknown tensor format")
}

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@ -1,163 +0,0 @@
package convert
import (
"bytes"
"encoding/binary"
"encoding/json"
"errors"
"fmt"
"io"
"io/fs"
"slices"
"strings"
"github.com/d4l3k/go-bfloat16"
"github.com/x448/float16"
"golang.org/x/exp/maps"
)
type safetensorMetadata struct {
Type string `json:"dtype"`
Shape []uint64 `json:"shape"`
Offsets []int64 `json:"data_offsets"`
}
func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]Tensor, error) {
var ts []Tensor
for _, p := range ps {
f, err := fsys.Open(p)
if err != nil {
return nil, err
}
defer f.Close()
var n int64
if err := binary.Read(f, binary.LittleEndian, &n); err != nil {
return nil, err
}
b := bytes.NewBuffer(make([]byte, 0, n))
if _, err = io.CopyN(b, f, n); err != nil {
return nil, err
}
var headers map[string]safetensorMetadata
if err := json.NewDecoder(b).Decode(&headers); err != nil {
return nil, err
}
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,
shape: value.Shape,
},
})
}
}
}
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
}
type safetensor struct {
fs fs.FS
path string
dtype string
offset int64
size int64
*tensorBase
}
func (st safetensor) WriteTo(w io.Writer) (int64, error) {
f, err := st.fs.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
}
}
var f32s []float32
switch st.dtype {
case "F32":
f32s = make([]float32, st.size/4)
if err = binary.Read(f, binary.LittleEndian, f32s); err != nil {
return 0, err
}
case "F16":
u16s := make([]uint16, st.size/2)
if err = binary.Read(f, binary.LittleEndian, u16s); err != nil {
return 0, err
}
f32s = make([]float32, len(u16s))
for i := range u16s {
f32s[i] = float16.Frombits(u16s[i]).Float32()
}
case "BF16":
u8s := make([]uint8, st.size)
if err = binary.Read(f, binary.LittleEndian, u8s); err != nil {
return 0, err
}
f32s = bfloat16.DecodeFloat32(u8s)
default:
return 0, fmt.Errorf("unknown data type: %s", st.dtype)
}
if st.repacker != nil {
f32s, err = st.repacker(st.Name(), f32s, st.Shape())
if err != nil {
return 0, err
}
}
switch st.Kind() {
case tensorKindF32:
return 0, binary.Write(w, binary.LittleEndian, f32s)
case tensorKindF16:
f16s := make([]uint16, len(f32s))
for i := range f32s {
f16s[i] = float16.Fromfloat32(f32s[i]).Bits()
}
return 0, binary.Write(w, binary.LittleEndian, f16s)
default:
return 0, fmt.Errorf("unknown storage type: %d", st.Kind())
}
}

View File

@ -1,48 +0,0 @@
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) {
var ts []Tensor
for _, p := range ps {
pt, err := pytorch.Load(p)
if err != nil {
return nil, err
}
for _, k := range pt.(*types.Dict).Keys() {
t := pt.(*types.Dict).MustGet(k)
var shape []uint64
for dim := range t.(*pytorch.Tensor).Size {
shape = append(shape, uint64(dim))
}
ts = append(ts, torch{
storage: t.(*pytorch.Tensor).Source,
tensorBase: &tensorBase{
name: replacer.Replace(k.(string)),
shape: shape,
},
})
}
}
return ts, nil
}
type torch struct {
storage pytorch.StorageInterface
*tensorBase
}
func (pt torch) WriteTo(w io.Writer) (int64, error) {
return 0, nil
}

309
convert/safetensors.go Normal file
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@ -0,0 +1,309 @@
package convert
import (
"bytes"
"encoding/binary"
"encoding/json"
"fmt"
"io"
"os"
"path/filepath"
"regexp"
"slices"
"strings"
"github.com/d4l3k/go-bfloat16"
"github.com/x448/float16"
"github.com/ollama/ollama/llm"
)
type safetensorWriterTo struct {
t *llm.Tensor
params *Params
bo ByteOrder
filename string
dtype string
offset, size int64
repacker func(string, []float32, []uint64) ([]float32, error)
}
type safetensorMetadata struct {
Type string `json:"dtype"`
Shape []uint64 `json:"shape"`
Offsets []int64 `json:"data_offsets"`
}
type SafetensorFormat struct{}
func (m *SafetensorFormat) GetTensors(dirpath string, params *Params) ([]llm.Tensor, error) {
var tensors []llm.Tensor
matches, err := filepath.Glob(filepath.Join(dirpath, "*.safetensors"))
if err != nil {
return nil, err
}
var offset uint64
for _, f := range matches {
var t []llm.Tensor
var err error
t, offset, err = m.readTensors(f, offset, params)
if err != nil {
return nil, err
}
tensors = append(tensors, t...)
}
return tensors, nil
}
func (m *SafetensorFormat) readTensors(fn string, offset uint64, params *Params) ([]llm.Tensor, uint64, error) {
f, err := os.Open(fn)
if err != nil {
return nil, 0, err
}
defer f.Close()
var n int64
if err := binary.Read(f, binary.LittleEndian, &n); err != nil {
return nil, 0, err
}
b := bytes.NewBuffer(make([]byte, 0, n))
if _, err = io.CopyN(b, f, n); err != nil {
return nil, 0, err
}
var headers map[string]safetensorMetadata
if err := json.NewDecoder(b).Decode(&headers); err != nil {
return nil, 0, err
}
var keys []string
for key := range headers {
if !strings.HasSuffix(key, "self_attn.rotary_embd.inv_freq") {
keys = append(keys, key)
}
}
slices.Sort(keys)
var tensors []llm.Tensor
for _, key := range keys {
value := headers[key]
var kind uint32
switch len(value.Shape) {
case 0:
// valuedata
continue
case 2:
kind = 1
}
name, err := m.GetLayerName(key)
if err != nil {
return nil, 0, err
}
shape := make([]uint64, len(value.Shape))
copy(shape, value.Shape)
pad := func(s int64) int64 {
return 8 + n + s
}
t := llm.Tensor{
Name: name,
Kind: kind,
Offset: offset,
Shape: shape[:],
}
t.WriterTo = safetensorWriterTo{
t: &t,
params: params,
bo: params.ByteOrder,
filename: fn,
dtype: value.Type,
offset: pad(value.Offsets[0]),
size: pad(value.Offsets[1]) - pad(value.Offsets[0]),
}
offset += t.Size()
tensors = append(tensors, t)
}
return tensors, offset, nil
}
func (m *SafetensorFormat) GetParams(dirpath string) (*Params, error) {
f, err := os.Open(filepath.Join(dirpath, "config.json"))
if err != nil {
return nil, err
}
defer f.Close()
var params Params
if err := json.NewDecoder(f).Decode(&params); err != nil {
return nil, err
}
params.ByteOrder = binary.LittleEndian
return &params, nil
}
func (m *SafetensorFormat) GetLayerName(n string) (string, error) {
directMap := map[string]string{
"model.embed_tokens.weight": "token_embd.weight",
"lm_head.weight": "output.weight",
"model.norm.weight": "output_norm.weight",
}
tMap := map[string]string{
"model.layers.(\\d+).input_layernorm.weight": "blk.$1.attn_norm.weight",
"model.layers.(\\d+).mlp.down_proj.weight": "blk.$1.ffn_down.weight",
"model.layers.(\\d+).mlp.gate_proj.weight": "blk.$1.ffn_gate.weight",
"model.layers.(\\d+).mlp.up_proj.weight": "blk.$1.ffn_up.weight",
"model.layers.(\\d+).post_attention_layernorm.weight": "blk.$1.ffn_norm.weight",
"model.layers.(\\d+).self_attn.k_proj.weight": "blk.$1.attn_k.weight",
"model.layers.(\\d+).self_attn.o_proj.weight": "blk.$1.attn_output.weight",
"model.layers.(\\d+).self_attn.q_proj.weight": "blk.$1.attn_q.weight",
"model.layers.(\\d+).self_attn.v_proj.weight": "blk.$1.attn_v.weight",
"model.layers.(\\d+).block_sparse_moe.gate.weight": "blk.$1.ffn_gate_inp.weight",
"model.layers.(\\d+).block_sparse_moe.experts.(\\d+).w1.weight": "blk.$1.ffn_gate.$2.weight",
"model.layers.(\\d+).block_sparse_moe.experts.(\\d+).w2.weight": "blk.$1.ffn_down.$2.weight",
"model.layers.(\\d+).block_sparse_moe.experts.(\\d+).w3.weight": "blk.$1.ffn_up.$2.weight",
}
v, ok := directMap[n]
if ok {
return v, nil
}
// quick hack to rename the layers to gguf format
for k, v := range tMap {
re := regexp.MustCompile(k)
newName := re.ReplaceAllString(n, v)
if newName != n {
return newName, nil
}
}
return "", fmt.Errorf("couldn't find a layer name for '%s'", n)
}
func (r safetensorWriterTo) WriteTo(w io.Writer) (n int64, err error) {
f, err := os.Open(r.filename)
if err != nil {
return 0, err
}
defer f.Close()
if _, err = f.Seek(r.offset, io.SeekStart); err != nil {
return 0, err
}
var f32s []float32
switch r.dtype {
case "F32":
f32s = make([]float32, r.size/4)
if err = binary.Read(f, r.bo, f32s); err != nil {
return 0, err
}
case "F16":
u16s := make([]uint16, r.size/2)
if err = binary.Read(f, r.bo, u16s); err != nil {
return 0, err
}
for _, b := range u16s {
f32s = append(f32s, float16.Frombits(b).Float32())
}
case "BF16":
u8s := make([]uint8, r.size)
if err = binary.Read(f, r.bo, u8s); err != nil {
return 0, err
}
f32s = bfloat16.DecodeFloat32(u8s)
default:
return 0, fmt.Errorf("unknown data type: %s", r.dtype)
}
if r.repacker != nil {
f32s, err = r.repacker(r.t.Name, f32s, r.t.Shape)
if err != nil {
return 0, err
}
}
switch r.t.Kind {
case 0:
return 0, binary.Write(w, r.bo, f32s)
case 1:
f16s := make([]uint16, len(f32s))
for i := range f32s {
f16s[i] = float16.Fromfloat32(f32s[i]).Bits()
}
return 0, binary.Write(w, r.bo, f16s)
default:
return 0, fmt.Errorf("unknown storage type: %d", r.t.Kind)
}
}
func (m *SafetensorFormat) GetModelArch(name, dirPath string, params *Params) (ModelArch, error) {
switch len(params.Architectures) {
case 0:
return nil, fmt.Errorf("No architecture specified to convert")
case 1:
switch params.Architectures[0] {
case "LlamaForCausalLM":
return &LlamaModel{
ModelData{
Name: name,
Path: dirPath,
Params: params,
Format: m,
},
}, nil
case "MistralForCausalLM":
return &MistralModel{
ModelData{
Name: name,
Path: dirPath,
Params: params,
Format: m,
},
}, nil
case "MixtralForCausalLM":
return &MixtralModel{
ModelData{
Name: name,
Path: dirPath,
Params: params,
Format: m,
},
}, nil
case "GemmaForCausalLM":
return &GemmaModel{
ModelData{
Name: name,
Path: dirPath,
Params: params,
Format: m,
},
}, nil
default:
return nil, fmt.Errorf("Models based on '%s' are not yet supported", params.Architectures[0])
}
}
return nil, fmt.Errorf("Unknown error")
}

View File

@ -1,313 +0,0 @@
{
"general.architecture": "llama",
"general.file_type": "1",
"general.quantization_version": "2",
"llama.block_count": "32",
"llama.context_length": "8192",
"llama.embedding_length": "4096",
"llama.feed_forward_length": "14336",
"llama.rope.dimension_count": "128",
"llama.rope.freq_base": "500000",
"llama.vocab_size": "128256",
"llama.attention.head_count": "32",
"llama.attention.head_count_kv": "8",
"llama.attention.layer_norm_rms_epsilon": "1e-05",
"tokenizer.ggml.model": "gpt2",
"tokenizer.ggml.pre": "llama-bpe",
"tokenizer.ggml.bos_token_id": "128000",
"tokenizer.ggml.eos_token_id": "128009",
"tokenizer.ggml.merges": "d0cbac1fcc9dcf03724b8db5c9bfb593ae1cf68fb9bc72eb1d15274dcbbf618b",
"tokenizer.ggml.token_type": "d70a88809fd7da6f1f028622685cd64268a7a922c5d343c96f25b66327358978",
"tokenizer.ggml.tokens": "765b529dbcbc42dd202ce657341c63807b51f3b07e09898f6aa6196326865d5a",
"token_embd.weight": "b53102a11d9064bbd404833e3464b1b13e08ce73300b442312cccde2f19b2698",
"blk.0.attn_norm.weight": "7318df3cca9e8d153ff0a503026a1265e63d20b2a8c1dd7a2769585082b5d1ee",
"blk.0.ffn_down.weight": "b950806a1fc722c9fad7fd0b20c3c0a7fb50f14395e1e7663a590bfd62e20900",
"blk.0.ffn_gate.weight": "e73e580af6d4f08e060a74a3c25efdf5d3bed99e183d95a5a85ae859014839fd",
"blk.0.ffn_up.weight": "c8158af679ef99746da1befb67eebb19489e0bbe6ce7d97e13e348508244e516",
"blk.0.ffn_norm.weight": "7ec69c3c31e95e49a3359003b0033f6b9e85561a3e3fd83e7476661ecdd756bb",
"blk.0.attn_k.weight": "2732303257bac969b4964e0e32ec08b5a7f5c031bb02bf6ac4467b3ea0ebcf1e",
"blk.0.attn_output.weight": "ecda1d43b4ccc91cd5b366d7e7a275353990ac78561a07c83d9c77031aba12dc",
"blk.0.attn_q.weight": "569b1f5faf92b6f00910cf7effb2d5862f91038ce5c3b0019fc10e5d79fbd5e1",
"blk.0.attn_v.weight": "aa8416c5ef7e32fb54a1f20d6ac651656845d4af240564b397c39bd83e06e3b8",
"blk.1.attn_norm.weight": "03327e02862908c2a44b2f52decdb924bf4201f400b46f8037a9cb2e1d7a61ff",
"blk.1.ffn_down.weight": "5a83a87603f38c99f8e1e370a2d5f967bb45ac51d881a609304a7811027321e0",
"blk.1.ffn_gate.weight": "31da0572c79e655186c721c231376f85e56cdcc6257c28d08c8c5b40d5c22b40",
"blk.1.ffn_up.weight": "e0c811d64ca155c8de10a868e72015d43888834804614ee1aa2953129ffbc90f",
"blk.1.ffn_norm.weight": "5861f313d6137d6f0f904d423df47fffc6069e224ff746e1b637ac9c7f0af862",
"blk.1.attn_k.weight": "5fbbec0acca6457b9416ebdcd90e526885d0224537b7628f6be376a7f275313d",
"blk.1.attn_output.weight": "b237c9763fa3f75166a6f70b70f1566e77d0d89dfa164ed1b3137393e90575c3",
"blk.1.attn_q.weight": "c0a9cf4a98b4882b16f3eb2b49d933793dcc5357abb246fd3fe3134ed2b12e1c",
"blk.1.attn_v.weight": "96867111727200cac1af7865189dd41fd62b47584e5e5f33a91f1d34509cbd40",
"blk.2.attn_norm.weight": "f392f8a88ee3a95b1cc19c40dd4ef66317037b0faaa1800f610779e129ee0539",
"blk.2.ffn_down.weight": "73823eef46632aedcc8c1cb08a736b6aa97ca97842cd1fdfc5567d8dec459662",
"blk.2.ffn_gate.weight": "f4909ae19fc3848b00bb8b9050122e74f8e903b89e22937036f4cc9fea20a718",
"blk.2.ffn_up.weight": "16f4904a3d814ea68f00519724fc4943e48444a84c786bda39aa5efc298a7d84",
"blk.2.ffn_norm.weight": "e3ccdf56e75cb969f6f69c39caf6daf7c4e70e89e25df0f4d2e4bc60e159aafe",
"blk.2.attn_k.weight": "c3beb1e0a11bcf007ef0f0d8f6bdd3082d8b29090cd29597846b5d51e308a8e5",
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}

View File

@ -1,3 +0,0 @@
{
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}

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@ -1,313 +0,0 @@
{
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}

View File

@ -1,348 +0,0 @@
{
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}

View File

@ -1,225 +0,0 @@
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}

View File

@ -1,124 +0,0 @@
{
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}

View File

@ -1,312 +0,0 @@
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}

View File

@ -1,6 +0,0 @@
{
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}

View File

@ -1,188 +0,0 @@
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"blk.11.attn_output.weight": "e10725c7cf746ed4a7e472cf7aea6cb564e5db6a1d5197adc980d650a387ccea",
"blk.11.attn_q.weight": "05ee758a7d065802630f8c65dca424364c1c8825e389aa33f9405c45e8a50cce",
"blk.11.attn_v.weight": "0c3ae7090f11775d24c51120db6e305db6aff706493e7ee123dcab74485ba789",
"blk.11.ffn_down.weight": "7ba40b8e12c09c5fb2006b77a771cb01ce894e88a3b3e1877f927a5b89c91709",
"blk.11.ffn_gate.weight": "db76388a023b98097972d354ba1c6a5e26efdeb1c596b9c28bf2cd8f6596975e",
"blk.11.ffn_norm.weight": "a38c3ae1b89a68ddc7b72c99c5b28be7fe3787c4fad9904d0c43d64eaf00c474",
"blk.11.ffn_up.weight": "13c8142f9cf1eddc658babf978daf3515c4ccc45f849f3e7e3930aa18a8480a0",
"blk.12.attn_k.weight": "f03241c36ac87cb57429a2ef22186b8d7d0b590a8b173beb01fa13d93772f3b1",
"blk.12.attn_norm.weight": "4568f654e6d65104d586e7c16ba960c83428698ce103022b7e0be15e2884e13b",
"blk.12.attn_output.weight": "04867603f82f91e41306e09b33ecda0104b3ee4834061f2c0bbdc8da33c72509",
"blk.12.attn_q.weight": "70fe04b9a8e08b6100cc8d6b58bf4cbbad15ca1de82d63baca5d352ba6c4cbae",
"blk.12.attn_v.weight": "15cb28db61a86c98687991d7e611bc92a1fcc6007f3432149cfb5fe518a4f65e",
"blk.12.ffn_down.weight": "6d10c790a4e3dc44c2dc36d96251ae97cdf30a4fa04d4c43e31bfbd038e6a7b7",
"blk.12.ffn_gate.weight": "3462a2d8f6b4743b25e24da51b90018ac2858d05ac7e582bcb69063cfdac1104",
"blk.12.ffn_norm.weight": "1f96392c1faa34e34ae5dea55a6a86c5aa4c79758952075d53d28de89dd88456",
"blk.12.ffn_up.weight": "d22eacc612a7411953d948483c5fb201e11722955ee0754da866e7bec578ac6d",
"blk.13.attn_k.weight": "5864977e6b733ea942647d6feed5c76156c48c200649c22e4e11b9e5860e57f3",
"blk.13.attn_norm.weight": "87e053535144723db4145aa5402acc54331b7696752d852bb9fc542ff33f0fb5",
"blk.13.attn_output.weight": "078145f5ad83f8b14f97a869346f7fd1583b24d1e3edadaa95d3da4242973f8f",
"blk.13.attn_q.weight": "3b8caf35504cbc4d1a7dd6e011a95760703b7f71e2218b030b1254f811362dd7",
"blk.13.attn_v.weight": "4fdf8365a603e043e5b40c4a21c84ac167f9be62794178f9d8a608dfe5653bf9",
"blk.13.ffn_down.weight": "a07d3abbfcacf48ba028df2cab895be32cc15022d23389a745286e79c1b1d1fd",
"blk.13.ffn_gate.weight": "1d2ab39666aa2909acc96787432a3ed13b19d25170f74665fadff9b17bbaffb1",
"blk.13.ffn_norm.weight": "4f2e809fda5f3eadf52578ee50e0ba36e53be91e55dce418c12dfe595f5f18e7",
"blk.13.ffn_up.weight": "8783d2720c2c37ca176a5801e0b3ef1f9cc9cf3ef1cd37af423aaf6b2a27e2bd",
"blk.14.attn_k.weight": "ce9428e2b55d43ae0c6690dbd56182f99adc427694ba8236b405cc8ea5035e86",
"blk.14.attn_norm.weight": "6abb35f9db8251d6ae954bda147c6ada2371b0574d11702e828f3c6ac99b7cc0",
"blk.14.attn_output.weight": "fe3880916d0ceb5bff672c88bbefb7060a545be609bf049beb2024b38221836d",
"blk.14.attn_q.weight": "7c8ad81be6f4a350931fd108b5f7c9e366e8c26ef62d1d85ffef5dca8fd893f8",
"blk.14.attn_v.weight": "e4bdedffacbebe38567a0734dfd67db90e911d9a9669fcde9a7c4ad8a0066c52",
"blk.14.ffn_down.weight": "ef6694dff1e05820aac0cd2b22f39ac7788b4967afc9250775575554c66aab2c",
"blk.14.ffn_gate.weight": "db63c4179e2db704bc505e2b4696e055b593e295a1b7c4c586fc793bdd5aab19",
"blk.14.ffn_norm.weight": "2796a62d832a9710148f95d533320492a33e712b2e5218659c548705bd11684d",
"blk.14.ffn_up.weight": "3f78c78d8c2d54df45f799d4ff902316628af296834afe4ceed63d4a324ff03e",
"blk.15.attn_k.weight": "6e810ee3859e07695645ee0c9a5efc7962668984a5f0a9325f47e462743b447c",
"blk.15.attn_norm.weight": "0956b576ae96db0b28cb09f761f801cfd9281432284664f0fe181c8d9c55d1ec",
"blk.15.attn_output.weight": "03a17f7e94208177aace5cc41b7f54670ba57873b7274ff6e23caf58cce110ca",
"blk.15.attn_q.weight": "b8edafe7d2216a6f8b4ae4905a906475490e6ea418f6e1d3cec563dbdc6fab91",
"blk.15.attn_v.weight": "f8ae8cae0f4cfa34a459824eba57350c3c248104ba5607e7d9dc7d7c39aaf4a6",
"blk.15.ffn_down.weight": "8d02eb439da852246d2ca67e9b7b6de0b090b80744355e64728a23e41926505b",
"blk.15.ffn_gate.weight": "ed5bf361c67db8731f186b775826f21c33bdb521111fd2d922539719a770239f",
"blk.15.ffn_norm.weight": "5942ca3c73209ac9a0c8bfd9b4aab7f7be7aee9aa12d9c35833493b44af76767",
"blk.15.ffn_up.weight": "f4bebf4ad99ec5f911327dec347be6c595814885309c7bc5647ce28c7f4d1cf5",
"blk.16.attn_k.weight": "756a534c19364448e0958b8948fe33891c6ccda0fbb4dfa2024e1f532a87804b",
"blk.16.attn_norm.weight": "386b7b9e4e6509f6af9c022d942b6c6c6cc136aeed8751ecb037c74d7c4bfb93",
"blk.16.attn_output.weight": "3ba1a766a25830b84d7c22178203635f9c5624caad290bc5e5d73da5d5e7a2ec",
"blk.16.attn_q.weight": "d39b0c91e1fda7685d50a0f7cc8d18c44b5bdc90a142c7fda0bc329cca1afa74",
"blk.16.attn_v.weight": "98b33fcb0ee3483cff1b06ecb44d7b7ffb4d34c268248e4d73dfdf82b2065b2f",
"blk.16.ffn_down.weight": "14006f5e4acb2f9416271ae562e299359cd2585739c7fc77ccbca54495563948",
"blk.16.ffn_gate.weight": "12f8abae2d301d8f88bedb6af98b1daecc7b0b8d05148594f931f30958d77aca",
"blk.16.ffn_norm.weight": "129a15a046ee96d06de288bd43c80f77a6b0fb3a159c7367154c6e4aaf362672",
"blk.16.ffn_up.weight": "b4a5911a45f3871ef1d4efb7dc7108645a564b70f818eccf45beebef2e844ee9",
"blk.17.attn_k.weight": "5e1bfcff0146ebdde3817b656952892eb671e14e75afc92fa53f84f8eecbec4c",
"blk.17.attn_norm.weight": "60bc988fab7c4b29ee9de599df41a8de00caa94fcd74677da011fac82f60f465",
"blk.17.attn_output.weight": "ba49b40d6a0b5685f749c24b0edbed3adc44dbe13b5d5e5fa1e56169fc746555",
"blk.17.attn_q.weight": "82bb415d24efcd14d03ace03f907bb70db6a204c76a0bdd1892e0fba165db87d",
"blk.17.attn_v.weight": "73dbe54beb91a899884e275ea81ffc5187a20cb7d5b68d5c299b783096999d94",
"blk.17.ffn_down.weight": "7c086166241e0664f8963fd1ca4ed74c737abfb2525ec20f8435821ff50158f3",
"blk.17.ffn_gate.weight": "51a32f78244d42a539f619c5ce661db9e6cf41636280a826d439b5444edcd28c",
"blk.17.ffn_norm.weight": "c4bb247fccd1ecc84875028af63dd20aaf5cbd17eb94a9bc36679c09285dccab",
"blk.17.ffn_up.weight": "b5886182790bc6fbadd63de9bc4ffee416f3b69a66280d197ab8c18edf769abf",
"output_norm.weight": "481f3097d0a20412e35b3a739b1b958487bcd41ff67744baa3c9acbddd2ee4d4"
}

View File

@ -1,12 +1,10 @@
package convert
import (
"cmp"
"crypto/sha256"
"encoding/hex"
"encoding/json"
"errors"
"fmt"
"io/fs"
"log/slog"
"os"
"slices"
@ -14,152 +12,10 @@ import (
"golang.org/x/exp/maps"
)
const (
_ int32 = iota
tokenTypeNormal
tokenTypeUnknown
tokenTypeControl
tokenTypeUserDefined
tokenTypeUnused
tokenTypeByte
)
type Tokenizer struct {
*Vocabulary
SpecialVocabulary []*SpecialVocabulary
Merges []string
Pre string
Template string
}
func parseTokenizer(fsys fs.FS, specialTokenTypes []string) (*Tokenizer, error) {
v, err := parseVocabulary(fsys)
if err != nil {
return nil, err
}
t := &Tokenizer{
Vocabulary: v,
Pre: "default",
}
addedTokens := make(map[string]token)
if f, err := fsys.Open("tokenizer.json"); errors.Is(err, os.ErrNotExist) {
} else if err != nil {
return nil, err
} else {
defer f.Close()
var tt tokenizer
if err := json.NewDecoder(f).Decode(&tt); err != nil {
return nil, err
}
for _, t := range tt.AddedTokens {
addedTokens[t.Content] = t
}
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))
}
}
}
switch digest := hex.EncodeToString(sha256sum.Sum(nil)); digest {
case "d98f9631be1e9607a9848c26c1f9eac1aa9fc21ac6ba82a2fc0741af9780a48f":
t.Pre = "llama-bpe"
case "03df5c5863ad70781dcfdef491ead25140f895fe8010964be0daefe27be32b02":
t.Pre = "deepseek-llm"
case "21cde974d587f0d54dc8d56b183cc1e6239600172035c68fbd6d4b9f8da0576e":
t.Pre = "deepseek-coder"
case "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855":
// noop, empty pretokenizer
default:
slog.Warn("unknown pretokenizer, using default", "digest", digest)
}
}
if f, err := fsys.Open("tokenizer_config.json"); errors.Is(err, os.ErrNotExist) {
} else if err != nil {
return nil, err
} else {
defer f.Close()
var p map[string]json.RawMessage
if err := json.NewDecoder(f).Decode(&p); err != nil {
return nil, err
}
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)
}
}
for _, st := range specialTokenTypes {
sv := SpecialVocabulary{Type: st}
if bts, ok := p[fmt.Sprintf("add_%s_token", st)]; ok {
if err := json.Unmarshal(bts, &sv.AddToken); err != nil {
return nil, err
}
}
if bts, ok := p[fmt.Sprintf("%s_token", st)]; ok {
var content string
if err := json.Unmarshal(bts, &content); err != nil {
var mm map[string]any
if err := json.Unmarshal(bts, &mm); err != nil {
continue
}
content, ok = mm["content"].(string)
if !ok {
continue
}
}
sv.Content = content
}
if id, ok := addedTokens[sv.Content]; ok {
sv.ID = id.ID
t.SpecialVocabulary = append(t.SpecialVocabulary, &sv)
}
}
}
return t, nil
}
type tokenizer struct {
AddedTokens []token `json:"added_tokens"`
Model struct {
Type string `json:"type"`
Vocab map[string]int `json:"vocab"`
Merges []string `json:"merges"`
} `json:"model"`
Version string `json:"version"`
AddedTokens []Token `json:"added_tokens"`
Model TokenizerModel `json:"model"`
PreTokenizer struct {
PreTokenizers []struct {
@ -171,108 +27,83 @@ type tokenizer struct {
} `json:"pre_tokenizer"`
}
type token struct {
type TokenizerModel struct {
Type string `json:"type"`
Vocab map[string]int `json:"vocab"`
Merges []string `json:"merges"`
Tokens []Token
}
type Token struct {
ID int `json:"id"`
Content string `json:"content"`
Special bool `json:"special"`
UserDefined bool
}
type Vocabulary struct {
Model string
Tokens []string
Scores []float32
Types []int32
func (t *Token) Type() int32 {
switch {
case t.Special:
return tokenTypeControl
case t.UserDefined:
return tokenTypeUserDefined
default:
return tokenTypeNormal
}
}
func parseVocabularyFromTokenizer(fsys fs.FS) (*Vocabulary, error) {
f, err := fsys.Open("tokenizer.json")
func (t *Tokenizer) maxID() int {
return max(
slices.Max(maps.Values(t.Model.Vocab)),
slices.MaxFunc(t.AddedTokens, func(a, b Token) int {
return cmp.Compare(a.ID, b.ID)
}).ID,
)
}
func parseTokens(dirpath string) (pre string, tokens []Token, merges []string, err error) {
f, err := os.Open(dirpath)
if err != nil {
return nil, err
panic(err)
}
defer f.Close()
var t tokenizer
var t Tokenizer
if err := json.NewDecoder(f).Decode(&t); err != nil {
return nil, err
return "", nil, nil, err
}
tokens := make(map[int]token, len(t.Model.Vocab))
tokens = make([]Token, t.maxID()+1)
for k, v := range t.Model.Vocab {
tokens[v] = token{
ID: v,
Content: k,
tokens[v] = Token{ID: v, Content: k, Special: false, UserDefined: false}
}
for _, v := range t.AddedTokens {
v.UserDefined = true
tokens[v.ID] = v
}
sha256sum := sha256.New()
for _, pt := range t.PreTokenizer.PreTokenizers {
switch pt.Type {
case "Split":
if pt.Pattern.Regex != "" {
sha256sum.Write([]byte(pt.Pattern.Regex))
}
}
}
for _, token := range t.AddedTokens {
token.UserDefined = true
tokens[token.ID] = token
switch digest := fmt.Sprintf("%x", sha256sum.Sum(nil)); digest {
case "d98f9631be1e9607a9848c26c1f9eac1aa9fc21ac6ba82a2fc0741af9780a48f":
pre = "llama-bpe"
case "03df5c5863ad70781dcfdef491ead25140f895fe8010964be0daefe27be32b02":
pre = "deepseek-llm"
case "21cde974d587f0d54dc8d56b183cc1e6239600172035c68fbd6d4b9f8da0576e":
pre = "deepseek-coder"
default:
slog.Warn("unknown pretokenizer, using default", "digest", digest)
pre = "default"
}
keys := maps.Keys(tokens)
slices.Sort(keys)
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))
switch {
case token.Special:
v.Types = append(v.Types, tokenTypeControl)
case token.UserDefined:
v.Types = append(v.Types, tokenTypeUserDefined)
default:
v.Types = append(v.Types, tokenTypeNormal)
}
}
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},
}
for _, pattern := range patterns {
if _, err := fs.Stat(fsys, pattern.Pattern); errors.Is(err, os.ErrNotExist) {
continue
} else if err != nil {
return nil, err
}
return pattern.Func(fsys)
}
return nil, errors.New("unknown tokenizer format")
}
type SpecialVocabulary struct {
Type string
ID int
Content string
AddToken bool
}
func (sv SpecialVocabulary) Key() string {
switch t := sv.Type; t {
case "bos", "eos", "cls", "mask":
return t
case "unk":
return "unknown"
case "sep":
//nolint:misspell // this is an upstream typo
return "seperator"
case "pad":
return "padding"
}
panic("unknown special vocabulary type")
return pre, tokens, t.Model.Merges, nil
}

View File

@ -1,113 +0,0 @@
package convert
import (
"cmp"
"encoding/json"
"errors"
"fmt"
"io/fs"
"os"
"slices"
"google.golang.org/protobuf/proto"
"github.com/ollama/ollama/convert/sentencepiece"
)
func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
ast, err := parseAdditionalSpecialTokens(fsys)
if err != nil {
return nil, err
}
bts, err := fs.ReadFile(fsys, "tokenizer.model")
if err != nil {
return nil, err
}
var spm sentencepiece.ModelProto
if err := proto.Unmarshal(bts, &spm); err != nil {
return nil, err
}
v := Vocabulary{Model: "llama"}
for _, piece := range spm.GetPieces() {
v.Tokens = append(v.Tokens, piece.GetPiece())
v.Scores = append(v.Scores, piece.GetScore())
switch t := piece.GetType(); t {
case sentencepiece.ModelProto_SentencePiece_UNKNOWN,
sentencepiece.ModelProto_SentencePiece_CONTROL,
sentencepiece.ModelProto_SentencePiece_UNUSED,
sentencepiece.ModelProto_SentencePiece_BYTE:
v.Types = append(v.Types, int32(t))
default:
tt := int32(sentencepiece.ModelProto_SentencePiece_NORMAL)
if slices.Contains(ast, piece.GetPiece()) {
tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)
}
v.Types = append(v.Types, tt)
}
}
f, err := fsys.Open("added_tokens.json")
if errors.Is(err, os.ErrNotExist) {
return &v, nil
} else if err != nil {
return nil, err
}
defer f.Close()
var atm map[string]int
if err := json.NewDecoder(f).Decode(&atm); err != nil {
return nil, err
}
type t struct {
id int
content string
}
var ts []t
for content, id := range atm {
ts = append(ts, t{id, content})
}
slices.SortFunc(ts, func(i, j t) int {
return cmp.Compare(i.id, j.id)
})
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)
v.Scores = append(v.Scores, -1000.0)
v.Types = append(v.Types, tokenTypeUserDefined)
}
return &v, nil
}
func parseAdditionalSpecialTokens(fsys fs.FS) ([]string, 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 []string `json:"additional_special_tokens"`
}
if err := json.NewDecoder(f).Decode(&m); err != nil {
return nil, err
}
return m.AdditionalSpecialTokens, nil
}

View File

@ -1,208 +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",
},
},
}
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)
}
})
}
}

288
convert/torch.go Normal file
View File

@ -0,0 +1,288 @@
package convert
import (
"encoding/binary"
"encoding/json"
"fmt"
"io"
"log/slog"
"os"
"path/filepath"
"regexp"
"strings"
"github.com/nlpodyssey/gopickle/pytorch"
"github.com/nlpodyssey/gopickle/types"
"github.com/x448/float16"
"github.com/ollama/ollama/llm"
)
type torchWriterTo struct {
t *llm.Tensor
params *Params
bo ByteOrder
storage pytorch.StorageInterface
repacker func(string, []float32, []uint64) ([]float32, error)
}
type TorchFormat struct{}
func (tf *TorchFormat) GetTensors(dirpath string, params *Params) ([]llm.Tensor, error) {
slog.Debug("getting torch tensors")
var files []string
if pt, _ := filepath.Glob(filepath.Join(dirpath, "consolidated*.pth")); len(pt) > 0 {
files = append(files, pt...)
} else if pt, _ := filepath.Glob(filepath.Join(dirpath, "pytorch_model*.pth")); len(pt) > 0 {
files = append(files, pt...)
}
var offset uint64
var tensors []llm.Tensor
for _, fn := range files {
m, err := pytorch.Load(fn)
if err != nil {
slog.Error(fmt.Sprintf("error unpickling: %q", err))
return []llm.Tensor{}, err
}
for _, k := range m.(*types.Dict).Keys() {
if strings.HasSuffix(k.(string), "self_attn.rotary_emb.inv_freq") {
continue
}
t, _ := m.(*types.Dict).Get(k)
tshape := t.(*pytorch.Tensor).Size
var size uint64
var kind uint32
switch len(tshape) {
case 0:
continue
case 1:
// convert to float32
kind = 0
size = uint64(tshape[0] * 4)
case 2:
// convert to float16
kind = 1
size = uint64(tshape[0] * tshape[1] * 2)
}
ggufName, err := tf.GetLayerName(k.(string))
if err != nil {
slog.Error(err.Error())
return nil, err
}
slog.Debug(fmt.Sprintf("'%35s': '%30s' %10d [%#v]", k.(string), ggufName, size, tshape))
shape := []uint64{0, 0, 0, 0}
for i := range tshape {
shape[i] = uint64(tshape[i])
}
tensor := llm.Tensor{
Name: ggufName,
Kind: kind,
Offset: offset, // calculate the offset
Shape: shape[:],
}
tensor.WriterTo = torchWriterTo{
t: &tensor,
params: params,
bo: params.ByteOrder,
storage: t.(*pytorch.Tensor).Source,
}
tensors = append(tensors, tensor)
offset += size
}
}
return tensors, nil
}
func getAltParams(dirpath string) (*Params, error) {
f, err := os.Open(filepath.Join(dirpath, "params.json"))
if err != nil {
slog.Error("no params.json")
return nil, err
}
defer f.Close()
type TorchParams struct {
HiddenSize int `json:"dim"`
AttentionHeads int `json:"n_heads"`
KeyValHeads int `json:"n_kv_heads"`
HiddenLayers int `json:"n_layers"`
RopeTheta float64 `json:"rope_theta"`
NormEPS float64 `json:"norm_eps"`
}
var tparams TorchParams
d := json.NewDecoder(f)
err = d.Decode(&tparams)
if err != nil {
return nil, err
}
params := &Params{
Architectures: []string{"LlamaForCausalLM"},
HiddenSize: tparams.HiddenSize,
AttentionHeads: tparams.AttentionHeads,
KeyValHeads: tparams.KeyValHeads,
HiddenLayers: tparams.HiddenLayers,
NormEPS: tparams.NormEPS,
}
switch {
case tparams.RopeTheta == 1000000:
// Codellama
params.ContextSize = 16384
case tparams.NormEPS == 1e-06:
// llama2
slog.Debug("Found llama2 - setting context size to 4096")
params.ContextSize = 4096
default:
params.ContextSize = 2048
}
params.ByteOrder = binary.LittleEndian
return params, nil
}
func (m *TorchFormat) GetParams(dirpath string) (*Params, error) {
f, err := os.Open(filepath.Join(dirpath, "config.json"))
if err != nil {
if os.IsNotExist(err) {
// try params.json instead
return getAltParams(dirpath)
} else {
return nil, err
}
}
var params Params
d := json.NewDecoder(f)
err = d.Decode(&params)
if err != nil {
return nil, err
}
params.ByteOrder = binary.LittleEndian
return &params, nil
}
func (m *TorchFormat) GetLayerName(n string) (string, error) {
directMap := map[string]string{
"tok_embeddings.weight": "token_embd.weight",
"output.weight": "output.weight",
"norm.weight": "output_norm.weight",
"rope.freqs": "rope_freqs.weight",
"model.embed_tokens.weight": "token_embd.weight",
"lm_head.weight": "output.weight",
"model.norm.weight": "output_norm.weight",
}
lMap := map[string]string{
"layers.(\\d+).attention_norm.weight": "blk.$1.attn_norm.weight",
"layers.(\\d+).attention_output_norm.weight": "blk.$1.attn_norm.weight",
"layers.(\\d+).feed_forward.w2.weight": "blk.$1.ffn_down.weight",
"layers.(\\d+).feed_forward.w1.weight": "blk.$1.ffn_gate.weight",
"layers.(\\d+).feed_forward.w3.weight": "blk.$1.ffn_up.weight",
"layers.(\\d+).ffn_norm.weight": "blk.$1.ffn_norm.weight",
"layers.(\\d+).attention.wk.weight": "blk.$1.attn_k.weight",
"layers.(\\d+).attention.wo.weight": "blk.$1.attn_output.weight",
"layers.(\\d+).attention.wq.weight": "blk.$1.attn_q.weight",
"layers.(\\d+).attention.wv.weight": "blk.$1.attn_v.weight",
"model.layers.(\\d+).input_layernorm.weight": "blk.$1.attn_norm.weight",
"model.layers.(\\d+).mlp.down_proj.weight": "blk.$1.ffn_down.weight",
"model.layers.(\\d+).mlp.gate_proj.weight": "blk.$1.ffn_gate.weight",
"model.layers.(\\d+).mlp.up_proj.weight": "blk.$1.ffn_up.weight",
"model.layers.(\\d+).post_attention_layernorm.weight": "blk.$1.ffn_norm.weight",
"model.layers.(\\d+).self_attn.k_proj.weight": "blk.$1.attn_k.weight",
"model.layers.(\\d+).self_attn.o_proj.weight": "blk.$1.attn_output.weight",
"model.layers.(\\d+).self_attn.q_proj.weight": "blk.$1.attn_q.weight",
"model.layers.(\\d+).self_attn.v_proj.weight": "blk.$1.attn_v.weight",
}
v, ok := directMap[n]
if ok {
return v, nil
}
// quick hack to rename the layers to gguf format
for k, v := range lMap {
re := regexp.MustCompile(k)
newName := re.ReplaceAllString(n, v)
if newName != n {
return newName, nil
}
}
return "", fmt.Errorf("couldn't find a layer name for '%s'", n)
}
func (r torchWriterTo) WriteTo(w io.Writer) (n int64, err error) {
var f32s []float32
switch s := r.storage.(type) {
case *pytorch.FloatStorage:
f32s = s.Data
case *pytorch.HalfStorage:
f32s = s.Data
case *pytorch.BFloat16Storage:
f32s = s.Data
default:
return 0, fmt.Errorf("unknown data type: %T", s)
}
if r.repacker != nil {
f32s, err = r.repacker(r.t.Name, f32s, r.t.Shape)
if err != nil {
return 0, err
}
}
switch r.t.Kind {
case 0:
return 0, binary.Write(w, r.bo, f32s)
case 1:
f16s := make([]uint16, len(f32s))
for i := range f32s {
f16s[i] = float16.Fromfloat32(f32s[i]).Bits()
}
return 0, binary.Write(w, r.bo, f16s)
default:
return 0, fmt.Errorf("unknown storage type: %d", r.t.Kind)
}
}
func (m *TorchFormat) GetModelArch(name, dirPath string, params *Params) (ModelArch, error) {
switch len(params.Architectures) {
case 0:
return nil, fmt.Errorf("No architecture specified to convert")
case 1:
switch params.Architectures[0] {
case "LlamaForCausalLM":
return &LlamaModel{
ModelData{
Name: name,
Path: dirPath,
Params: params,
Format: m,
},
}, nil
default:
return nil, fmt.Errorf("Models based on '%s' are not yet supported", params.Architectures[0])
}
}
return nil, fmt.Errorf("Unknown error")
}

View File

@ -1,535 +0,0 @@
package discover
import (
"bufio"
"errors"
"fmt"
"io"
"io/fs"
"log/slog"
"os"
"path/filepath"
"regexp"
"slices"
"sort"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
)
// Discovery logic for AMD/ROCm GPUs
const (
DriverVersionFile = "/sys/module/amdgpu/version"
AMDNodesSysfsDir = "/sys/class/kfd/kfd/topology/nodes/"
GPUPropertiesFileGlob = AMDNodesSysfsDir + "*/properties"
// Prefix with the node dir
GPUTotalMemoryFileGlob = "mem_banks/*/properties" // size_in_bytes line
// Direct Rendering Manager sysfs location
DRMDeviceDirGlob = "/sys/class/drm/card*/device"
DRMTotalMemoryFile = "mem_info_vram_total"
DRMUsedMemoryFile = "mem_info_vram_used"
// In hex; properties file is in decimal
DRMUniqueIDFile = "unique_id"
DRMVendorFile = "vendor"
DRMDeviceFile = "device"
)
var (
// Used to validate if the given ROCm lib is usable
ROCmLibGlobs = []string{"libhipblas.so.2*", "rocblas"} // TODO - probably include more coverage of files here...
RocmStandardLocations = []string{"/opt/rocm/lib", "/usr/lib64"}
)
// Gather GPU information from the amdgpu driver if any supported GPUs are detected
// Only called once during bootstrap
func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
resp := []RocmGPUInfo{}
if !AMDDetected() {
return resp, fmt.Errorf("AMD GPUs not detected")
}
// Opportunistic logging of driver version to aid in troubleshooting
driverMajor, driverMinor, err := AMDDriverVersion()
if err != nil {
// TODO - if we see users crash and burn with the upstreamed kernel this can be adjusted to hard-fail rocm support and fallback to CPU
slog.Warn("ollama recommends running the https://www.amd.com/en/support/linux-drivers", "error", err)
}
// Determine if the user has already pre-selected which GPUs to look at, then ignore the others
var visibleDevices []string
hipVD := envconfig.HipVisibleDevices() // zero based index only
rocrVD := envconfig.RocrVisibleDevices() // zero based index or UUID
gpuDO := envconfig.GpuDeviceOrdinal() // zero based index
switch {
case rocrVD != "":
visibleDevices = strings.Split(rocrVD, ",")
case hipVD != "":
visibleDevices = strings.Split(hipVD, ",")
case gpuDO != "":
visibleDevices = strings.Split(gpuDO, ",")
}
gfxOverride := envconfig.HsaOverrideGfxVersion()
var supported []string
libDir := ""
// The amdgpu driver always exposes the host CPU(s) first, but we have to skip them and subtract
// from the other IDs to get alignment with the HIP libraries expectations (zero is the first GPU, not the CPU)
matches, _ := filepath.Glob(GPUPropertiesFileGlob)
sort.Slice(matches, func(i, j int) bool {
// /sys/class/kfd/kfd/topology/nodes/<number>/properties
a, err := strconv.ParseInt(filepath.Base(filepath.Dir(matches[i])), 10, 64)
if err != nil {
slog.Debug("parse err", "error", err, "match", matches[i])
return false
}
b, err := strconv.ParseInt(filepath.Base(filepath.Dir(matches[j])), 10, 64)
if err != nil {
slog.Debug("parse err", "error", err, "match", matches[i])
return false
}
return a < b
})
gpuCount := 0
for _, match := range matches {
slog.Debug("evaluating amdgpu node " + match)
fp, err := os.Open(match)
if err != nil {
slog.Debug("failed to open sysfs node", "file", match, "error", err)
continue
}
defer fp.Close()
scanner := bufio.NewScanner(fp)
isCPU := false
var major, minor, patch uint64
var vendor, device, uniqueID uint64
for scanner.Scan() {
line := strings.TrimSpace(scanner.Text())
// Note: we could also use "cpu_cores_count X" where X is greater than zero to detect CPUs
if strings.HasPrefix(line, "gfx_target_version") {
ver := strings.Fields(line)
// Detect CPUs
if len(ver) == 2 && ver[1] == "0" {
slog.Debug("detected CPU " + match)
isCPU = true
break
}
if len(ver) != 2 || len(ver[1]) < 5 {
slog.Warn("malformed "+match, "gfx_target_version", line)
// If this winds up being a CPU, our offsets may be wrong
continue
}
l := len(ver[1])
var err1, err2, err3 error
patch, err1 = strconv.ParseUint(ver[1][l-2:l], 10, 32)
minor, err2 = strconv.ParseUint(ver[1][l-4:l-2], 10, 32)
major, err3 = strconv.ParseUint(ver[1][:l-4], 10, 32)
if err1 != nil || err2 != nil || err3 != nil {
slog.Debug("malformed int " + line)
continue
}
} else if strings.HasPrefix(line, "vendor_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "vendor_id", line)
continue
}
vendor, err = strconv.ParseUint(ver[1], 10, 64)
if err != nil {
slog.Debug("malformed", "vendor_id", line, "error", err)
}
} else if strings.HasPrefix(line, "device_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "device_id", line)
continue
}
device, err = strconv.ParseUint(ver[1], 10, 64)
if err != nil {
slog.Debug("malformed", "device_id", line, "error", err)
}
} else if strings.HasPrefix(line, "unique_id") {
ver := strings.Fields(line)
if len(ver) != 2 {
slog.Debug("malformed", "unique_id", line)
continue
}
uniqueID, err = strconv.ParseUint(ver[1], 10, 64)
if err != nil {
slog.Debug("malformed", "unique_id", line, "error", err)
}
}
// TODO - any other properties we want to extract and record?
// vendor_id + device_id -> pci lookup for "Name"
// Other metrics that may help us understand relative performance between multiple GPUs
}
// Note: while ./mem_banks/*/used_memory exists, it doesn't appear to take other VRAM consumers
// into consideration, so we instead map the device over to the DRM driver sysfs nodes which
// do reliably report VRAM usage.
if isCPU {
continue
}
// Skip over any GPUs that are masked
if major == 0 && minor == 0 && patch == 0 {
slog.Debug("skipping gpu with gfx000")
continue
}
// Keep track of numeric IDs based on valid GPUs
gpuID := gpuCount
gpuCount += 1
// Look up the memory for the current node
totalMemory := uint64(0)
usedMemory := uint64(0)
var usedFile string
mapping := []struct {
id uint64
filename string
}{
{vendor, DRMVendorFile},
{device, DRMDeviceFile},
{uniqueID, DRMUniqueIDFile}, // Not all devices will report this
}
slog.Debug("mapping amdgpu to drm sysfs nodes", "amdgpu", match, "vendor", vendor, "device", device, "unique_id", uniqueID)
// Map over to DRM location to find the total/free memory
drmMatches, _ := filepath.Glob(DRMDeviceDirGlob)
for _, devDir := range drmMatches {
matched := true
for _, m := range mapping {
if m.id == 0 {
// Null ID means it didn't populate, so we can't use it to match
continue
}
filename := filepath.Join(devDir, m.filename)
buf, err := os.ReadFile(filename)
if err != nil {
slog.Debug("failed to read sysfs node", "file", filename, "error", err)
matched = false
break
}
// values here are in hex, strip off the lead 0x and parse so we can compare the numeric (decimal) values in amdgpu
cmp, err := strconv.ParseUint(strings.TrimPrefix(strings.TrimSpace(string(buf)), "0x"), 16, 64)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", filename, "error", err)
matched = false
break
}
if cmp != m.id {
matched = false
break
}
}
if !matched {
continue
}
// Found the matching DRM directory
slog.Debug("matched", "amdgpu", match, "drm", devDir)
totalFile := filepath.Join(devDir, DRMTotalMemoryFile)
buf, err := os.ReadFile(totalFile)
if err != nil {
slog.Debug("failed to read sysfs node", "file", totalFile, "error", err)
break
}
totalMemory, err = strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", totalFile, "error", err)
break
}
usedFile = filepath.Join(devDir, DRMUsedMemoryFile)
usedMemory, err = getFreeMemory(usedFile)
if err != nil {
slog.Debug("failed to update used memory", "error", err)
}
break
}
var name string
// TODO - PCI ID lookup
if vendor > 0 && device > 0 {
name = fmt.Sprintf("%04x:%04x", vendor, device)
}
// Favor UUIDs if available to reduce possibility of getting the numeric IDs wrong
var ID string
if uniqueID != 0 {
ID = fmt.Sprintf("GPU-%016x", uniqueID)
} else {
ID = strconv.Itoa(gpuID)
}
gpuInfo := RocmGPUInfo{
GpuInfo: GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: (totalMemory - usedMemory),
},
ID: ID,
Name: name,
Compute: fmt.Sprintf("gfx%d%x%x", major, minor, patch),
MinimumMemory: rocmMinimumMemory,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
},
usedFilepath: usedFile,
index: gpuID,
}
// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
if totalMemory < IGPUMemLimit {
reason := "unsupported Radeon iGPU detected skipping"
slog.Info(reason, "id", gpuID, "total", format.HumanBytes2(totalMemory))
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: reason,
})
continue
}
if int(major) < RocmComputeMin {
reason := fmt.Sprintf("amdgpu too old gfx%d%x%x", major, minor, patch)
slog.Warn(reason, "gpu", gpuID)
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: reason,
})
continue
}
slog.Debug("amdgpu memory", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
slog.Debug("amdgpu memory", "gpu", gpuID, "available", format.HumanBytes2(totalMemory-usedMemory))
// If the user wants to filter to a subset of devices, filter out if we aren't a match
if len(visibleDevices) > 0 {
include := false
for _, visible := range visibleDevices {
if visible == gpuInfo.ID || visible == strconv.Itoa(gpuInfo.index) {
include = true
break
}
}
if !include {
reason := "filtering out device per user request"
slog.Info(reason, "id", gpuInfo.ID, "visible_devices", visibleDevices)
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: reason,
})
continue
}
}
// Final validation is gfx compatibility - load the library if we haven't already loaded it
// even if the user overrides, we still need to validate the library
if libDir == "" {
libDir, err = AMDValidateLibDir()
if err != nil {
err = fmt.Errorf("unable to verify rocm library: %w", err)
slog.Warn(err.Error())
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: err.Error(),
})
return nil, err
}
}
gpuInfo.DependencyPath = []string{libDir}
if gfxOverride == "" {
// Only load supported list once
if len(supported) == 0 {
supported, err = GetSupportedGFX(libDir)
if err != nil {
err = fmt.Errorf("failed to lookup supported GFX types: %w", err)
slog.Warn(err.Error())
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: err.Error(),
})
return nil, err
}
slog.Debug("rocm supported GPUs", "types", supported)
}
gfx := gpuInfo.Compute
if !slices.Contains[[]string, string](supported, gfx) {
reason := fmt.Sprintf("amdgpu is not supported (supported types:%s)", supported)
slog.Warn(reason, "gpu_type", gfx, "gpu", gpuInfo.ID, "library", libDir)
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: reason,
})
// TODO - consider discrete markdown just for ROCM troubleshooting?
slog.Warn("See https://github.com/ollama/ollama/blob/main/docs/gpu.md#overrides for HSA_OVERRIDE_GFX_VERSION usage")
continue
} else {
slog.Info("amdgpu is supported", "gpu", gpuInfo.ID, "gpu_type", gfx)
}
} else {
slog.Info("skipping rocm gfx compatibility check", "HSA_OVERRIDE_GFX_VERSION", gfxOverride)
}
// Check for env var workarounds
if name == "1002:687f" { // Vega RX 56
gpuInfo.EnvWorkarounds = append(gpuInfo.EnvWorkarounds, [2]string{"HSA_ENABLE_SDMA", "0"})
}
// The GPU has passed all the verification steps and is supported
resp = append(resp, gpuInfo)
}
if len(resp) == 0 {
err := fmt.Errorf("no compatible amdgpu devices detected")
slog.Info(err.Error())
return nil, err
}
if err := verifyKFDDriverAccess(); err != nil {
err = fmt.Errorf("amdgpu devices detected but permission problems block access: %w", err)
slog.Error(err.Error())
return nil, err
}
return resp, nil
}
// Quick check for AMD driver so we can skip amdgpu discovery if not present
func AMDDetected() bool {
// Some driver versions (older?) don't have a version file, so just lookup the parent dir
sysfsDir := filepath.Dir(DriverVersionFile)
_, err := os.Stat(sysfsDir)
if errors.Is(err, os.ErrNotExist) {
slog.Debug("amdgpu driver not detected " + sysfsDir)
return false
} else if err != nil {
slog.Debug("error looking up amd driver", "path", sysfsDir, "error", err)
return false
}
return true
}
// Prefer to use host installed ROCm, as long as it meets our minimum requirements
// failing that, tell the user how to download it on their own
func AMDValidateLibDir() (string, error) {
libDir, err := commonAMDValidateLibDir()
if err == nil {
return libDir, nil
}
// Well known ollama installer path
installedRocmDir := "/usr/share/ollama/lib/rocm"
if rocmLibUsable(installedRocmDir) {
return installedRocmDir, nil
}
// If we still haven't found a usable rocm, the user will have to install it on their own
slog.Warn("amdgpu detected, but no compatible rocm library found. Either install rocm v6, or follow manual install instructions at https://github.com/ollama/ollama/blob/main/docs/linux.md#manual-install")
return "", errors.New("no suitable rocm found, falling back to CPU")
}
func AMDDriverVersion() (driverMajor, driverMinor int, err error) {
_, err = os.Stat(DriverVersionFile)
if err != nil {
return 0, 0, fmt.Errorf("amdgpu version file missing: %s %w", DriverVersionFile, err)
}
fp, err := os.Open(DriverVersionFile)
if err != nil {
return 0, 0, err
}
defer fp.Close()
verString, err := io.ReadAll(fp)
if err != nil {
return 0, 0, err
}
pattern := `\A(\d+)\.(\d+).*`
regex := regexp.MustCompile(pattern)
match := regex.FindStringSubmatch(string(verString))
if len(match) < 2 {
return 0, 0, fmt.Errorf("malformed version string %s", string(verString))
}
driverMajor, err = strconv.Atoi(match[1])
if err != nil {
return 0, 0, err
}
driverMinor, err = strconv.Atoi(match[2])
if err != nil {
return 0, 0, err
}
return driverMajor, driverMinor, nil
}
func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
if len(gpus) == 0 {
return nil
}
for i := range gpus {
usedMemory, err := getFreeMemory(gpus[i].usedFilepath)
if err != nil {
return err
}
slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(gpus[i].TotalMemory-usedMemory))
gpus[i].FreeMemory = gpus[i].TotalMemory - usedMemory
}
return nil
}
func getFreeMemory(usedFile string) (uint64, error) {
buf, err := os.ReadFile(usedFile)
if err != nil {
return 0, fmt.Errorf("failed to read sysfs node %s %w", usedFile, err)
}
usedMemory, err := strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
if err != nil {
slog.Debug("failed to parse sysfs node", "file", usedFile, "error", err)
return 0, fmt.Errorf("failed to parse sysfs node %s %w", usedFile, err)
}
return usedMemory, nil
}
func verifyKFDDriverAccess() error {
// Verify we have permissions - either running as root, or we have group access to the driver
fd, err := os.OpenFile("/dev/kfd", os.O_RDWR, 0o666)
if err != nil {
if errors.Is(err, fs.ErrPermission) {
return fmt.Errorf("permissions not set up properly. Either run ollama as root, or add you user account to the render group. %w", err)
} else if errors.Is(err, fs.ErrNotExist) {
// Container runtime failure?
return fmt.Errorf("kfd driver not loaded. If running in a container, remember to include '--device /dev/kfd --device /dev/dri'")
}
return fmt.Errorf("failed to check permission on /dev/kfd: %w", err)
}
fd.Close()
return nil
}
func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
ids := []string{}
for _, info := range gpuInfo {
if info.Library != "rocm" {
// TODO shouldn't happen if things are wired correctly...
slog.Debug("rocmGetVisibleDevicesEnv skipping over non-rocm device", "library", info.Library)
continue
}
ids = append(ids, info.ID)
}
// There are 3 potential env vars to use to select GPUs.
// ROCR_VISIBLE_DEVICES supports UUID or numeric so is our preferred on linux
// GPU_DEVICE_ORDINAL supports numeric IDs only
// HIP_VISIBLE_DEVICES supports numeric IDs only
return "ROCR_VISIBLE_DEVICES", strings.Join(ids, ",")
}

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@ -1,220 +0,0 @@
package discover
import (
"bytes"
"errors"
"fmt"
"log/slog"
"os"
"path/filepath"
"slices"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
)
const (
// TODO We're lookinng for this exact name to detect iGPUs since hipGetDeviceProperties never reports integrated==true
iGPUName = "AMD Radeon(TM) Graphics"
)
var (
// Used to validate if the given ROCm lib is usable
ROCmLibGlobs = []string{"hipblas.dll", "rocblas"} // This is not sufficient to discern v5 vs v6
RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\6.1\\bin"} // TODO glob?
)
// Only called once during bootstrap
func AMDGetGPUInfo() ([]RocmGPUInfo, error) {
resp := []RocmGPUInfo{}
hl, err := NewHipLib()
if err != nil {
slog.Debug(err.Error())
return nil, err
}
defer hl.Release()
driverMajor, driverMinor, err := hl.AMDDriverVersion()
if err != nil {
// For now this is benign, but we may eventually need to fail compatibility checks
slog.Debug("error looking up amd driver version", "error", err)
}
// Note: the HIP library automatically handles subsetting to any *_VISIBLE_DEVICES the user specified
count := hl.HipGetDeviceCount()
if count == 0 {
err := fmt.Errorf("no compatible amdgpu devices detected")
slog.Info(err.Error())
return nil, err
}
libDir, err := AMDValidateLibDir()
if err != nil {
err = fmt.Errorf("unable to verify rocm library: %w", err)
slog.Warn(err.Error())
return nil, err
}
var supported []string
gfxOverride := envconfig.HsaOverrideGfxVersion()
if gfxOverride == "" {
supported, err = GetSupportedGFX(libDir)
if err != nil {
err = fmt.Errorf("failed to lookup supported GFX types: %w", err)
slog.Warn(err.Error())
return nil, err
}
} else {
slog.Info("skipping rocm gfx compatibility check", "HSA_OVERRIDE_GFX_VERSION", gfxOverride)
}
slog.Debug("detected hip devices", "count", count)
// TODO how to determine the underlying device ID when visible devices is causing this to subset?
for i := range count {
err = hl.HipSetDevice(i)
if err != nil {
slog.Warn("set device", "id", i, "error", err)
continue
}
props, err := hl.HipGetDeviceProperties(i)
if err != nil {
slog.Warn("get properties", "id", i, "error", err)
continue
}
n := bytes.IndexByte(props.Name[:], 0)
name := string(props.Name[:n])
// TODO is UUID actually populated on windows?
// Can luid be used on windows for setting visible devices (and is it actually set?)
n = bytes.IndexByte(props.GcnArchName[:], 0)
gfx := string(props.GcnArchName[:n])
slog.Debug("hip device", "id", i, "name", name, "gfx", gfx)
// slog.Info(fmt.Sprintf("[%d] Integrated: %d", i, props.iGPU)) // DOESN'T REPORT CORRECTLY! Always 0
// TODO Why isn't props.iGPU accurate!?
freeMemory, totalMemory, err := hl.HipMemGetInfo()
if err != nil {
slog.Warn("get mem info", "id", i, "error", err)
continue
}
gpuInfo := RocmGPUInfo{
GpuInfo: GpuInfo{
Library: "rocm",
memInfo: memInfo{
TotalMemory: totalMemory,
FreeMemory: freeMemory,
},
// Free memory reporting on Windows is not reliable until we bump to ROCm v6.2
UnreliableFreeMemory: true,
ID: strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
DependencyPath: []string{libDir},
MinimumMemory: rocmMinimumMemory,
Name: name,
Compute: gfx,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
},
index: i,
}
// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
if strings.EqualFold(name, iGPUName) || totalMemory < IGPUMemLimit {
reason := "unsupported Radeon iGPU detected skipping"
slog.Info(reason, "id", gpuInfo.ID, "total", format.HumanBytes2(totalMemory))
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: reason,
})
continue
}
// Strip off Target Features when comparing
if !slices.Contains[[]string, string](supported, strings.Split(gfx, ":")[0]) {
reason := fmt.Sprintf("amdgpu is not supported (supported types:%s)", supported)
slog.Warn(reason, "gpu_type", gfx, "gpu", gpuInfo.ID, "library", libDir)
unsupportedGPUs = append(unsupportedGPUs, UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
Reason: reason,
})
// HSA_OVERRIDE_GFX_VERSION not supported on windows
continue
} else {
slog.Debug("amdgpu is supported", "gpu", i, "gpu_type", gfx)
}
slog.Debug("amdgpu memory", "gpu", i, "total", format.HumanBytes2(totalMemory))
slog.Debug("amdgpu memory", "gpu", i, "available", format.HumanBytes2(freeMemory))
resp = append(resp, gpuInfo)
}
return resp, nil
}
func AMDValidateLibDir() (string, error) {
libDir, err := commonAMDValidateLibDir()
if err == nil {
return libDir, nil
}
// Installer payload (if we're running from some other location)
localAppData := os.Getenv("LOCALAPPDATA")
appDir := filepath.Join(localAppData, "Programs", "Ollama")
rocmTargetDir := filepath.Join(appDir, envconfig.LibRelativeToExe(), "lib", "ollama")
if rocmLibUsable(rocmTargetDir) {
slog.Debug("detected ollama installed ROCm at " + rocmTargetDir)
return rocmTargetDir, nil
}
// Should not happen on windows since we include it in the installer, but stand-alone binary might hit this
slog.Warn("amdgpu detected, but no compatible rocm library found. Please install ROCm")
return "", errors.New("no suitable rocm found, falling back to CPU")
}
func (gpus RocmGPUInfoList) RefreshFreeMemory() error {
if len(gpus) == 0 {
return nil
}
hl, err := NewHipLib()
if err != nil {
slog.Debug(err.Error())
return nil
}
defer hl.Release()
for i := range gpus {
err := hl.HipSetDevice(gpus[i].index)
if err != nil {
return err
}
freeMemory, _, err := hl.HipMemGetInfo()
if err != nil {
slog.Warn("get mem info", "id", i, "error", err)
continue
}
slog.Debug("updating rocm free memory", "gpu", gpus[i].ID, "name", gpus[i].Name, "before", format.HumanBytes2(gpus[i].FreeMemory), "now", format.HumanBytes2(freeMemory))
gpus[i].FreeMemory = freeMemory
}
return nil
}
func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
ids := []string{}
for _, info := range gpuInfo {
if info.Library != "rocm" {
// TODO shouldn't happen if things are wired correctly...
slog.Debug("rocmGetVisibleDevicesEnv skipping over non-rocm device", "library", info.Library)
continue
}
ids = append(ids, info.ID)
}
// There are 3 potential env vars to use to select GPUs.
// ROCR_VISIBLE_DEVICES supports UUID or numeric but does not work on Windows
// HIP_VISIBLE_DEVICES supports numeric IDs only
// GPU_DEVICE_ORDINAL supports numeric IDs only
return "HIP_VISIBLE_DEVICES", strings.Join(ids, ",")
}

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@ -1,37 +0,0 @@
package discover
import (
"os"
"path/filepath"
"runtime"
"strings"
"golang.org/x/sys/cpu"
)
func GetCPUCapability() CPUCapability {
if cpu.X86.HasAVX2 {
return CPUCapabilityAVX2
}
if cpu.X86.HasAVX {
return CPUCapabilityAVX
}
// else LCD
return CPUCapabilityNone
}
func IsNUMA() bool {
if runtime.GOOS != "linux" {
// numa support in llama.cpp is linux only
return false
}
ids := map[string]interface{}{}
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
}

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@ -1,64 +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))
}
}
}
}
}
if gpuInfo.computeMajor < 6 || gpuInfo.DriverMajor < 12 || (gpuInfo.DriverMajor == 12 && gpuInfo.DriverMinor == 0) {
return "v11"
}
return "v12"
}

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@ -1,754 +0,0 @@
//go:build linux || windows
package discover
/*
#cgo linux LDFLAGS: -lrt -lpthread -ldl -lstdc++ -lm
#cgo windows LDFLAGS: -lpthread
#include "gpu_info.h"
*/
import "C"
import (
"fmt"
"log/slog"
"os"
"path/filepath"
"runtime"
"strings"
"sync"
"unsafe"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
)
type cudaHandles struct {
deviceCount int
cudart *C.cudart_handle_t
nvcuda *C.nvcuda_handle_t
nvml *C.nvml_handle_t
}
type oneapiHandles struct {
oneapi *C.oneapi_handle_t
deviceCount int
}
const (
cudaMinimumMemory = 457 * format.MebiByte
rocmMinimumMemory = 457 * format.MebiByte
// TODO OneAPI minimum memory
)
var (
gpuMutex sync.Mutex
bootstrapped bool
cpuCapability CPUCapability
cpus []CPUInfo
cudaGPUs []CudaGPUInfo
nvcudaLibPath string
cudartLibPath string
oneapiLibPath string
nvmlLibPath string
rocmGPUs []RocmGPUInfo
oneapiGPUs []OneapiGPUInfo
// If any discovered GPUs are incompatible, report why
unsupportedGPUs []UnsupportedGPUInfo
// Keep track of errors during bootstrapping so that if GPUs are missing
// they expected to be present this may explain why
bootstrapErrors []error
)
// With our current CUDA compile flags, older than 5.0 will not work properly
var CudaComputeMin = [2]C.int{5, 0}
var RocmComputeMin = 9
// TODO find a better way to detect iGPU instead of minimum memory
const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU
// Note: gpuMutex must already be held
func initCudaHandles() *cudaHandles {
// TODO - if the ollama build is CPU only, don't do these checks as they're irrelevant and confusing
cHandles := &cudaHandles{}
// Short Circuit if we already know which library to use
// ignore bootstrap errors in this case since we already recorded them
if nvmlLibPath != "" {
cHandles.nvml, _, _ = loadNVMLMgmt([]string{nvmlLibPath})
return cHandles
}
if nvcudaLibPath != "" {
cHandles.deviceCount, cHandles.nvcuda, _, _ = loadNVCUDAMgmt([]string{nvcudaLibPath})
return cHandles
}
if cudartLibPath != "" {
cHandles.deviceCount, cHandles.cudart, _, _ = loadCUDARTMgmt([]string{cudartLibPath})
return cHandles
}
slog.Debug("searching for GPU discovery libraries for NVIDIA")
var cudartMgmtPatterns []string
// Aligned with driver, we can't carry as payloads
nvcudaMgmtPatterns := NvcudaGlobs
if runtime.GOOS == "windows" {
localAppData := os.Getenv("LOCALAPPDATA")
cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", CudartMgmtName)}
}
libDir := LibraryDir()
if libDir != "" {
cudartMgmtPatterns = []string{filepath.Join(libDir, CudartMgmtName)}
}
cudartMgmtPatterns = append(cudartMgmtPatterns, CudartGlobs...)
if len(NvmlGlobs) > 0 {
nvmlLibPaths := FindGPULibs(NvmlMgmtName, NvmlGlobs)
if len(nvmlLibPaths) > 0 {
nvml, libPath, err := loadNVMLMgmt(nvmlLibPaths)
if nvml != nil {
slog.Debug("nvidia-ml loaded", "library", libPath)
cHandles.nvml = nvml
nvmlLibPath = libPath
}
if err != nil {
bootstrapErrors = append(bootstrapErrors, err)
}
}
}
nvcudaLibPaths := FindGPULibs(NvcudaMgmtName, nvcudaMgmtPatterns)
if len(nvcudaLibPaths) > 0 {
deviceCount, nvcuda, libPath, err := loadNVCUDAMgmt(nvcudaLibPaths)
if nvcuda != nil {
slog.Debug("detected GPUs", "count", deviceCount, "library", libPath)
cHandles.nvcuda = nvcuda
cHandles.deviceCount = deviceCount
nvcudaLibPath = libPath
return cHandles
}
if err != nil {
bootstrapErrors = append(bootstrapErrors, err)
}
}
cudartLibPaths := FindGPULibs(CudartMgmtName, cudartMgmtPatterns)
if len(cudartLibPaths) > 0 {
deviceCount, cudart, libPath, err := loadCUDARTMgmt(cudartLibPaths)
if cudart != nil {
slog.Debug("detected GPUs", "library", libPath, "count", deviceCount)
cHandles.cudart = cudart
cHandles.deviceCount = deviceCount
cudartLibPath = libPath
return cHandles
}
if err != nil {
bootstrapErrors = append(bootstrapErrors, err)
}
}
return cHandles
}
// Note: gpuMutex must already be held
func initOneAPIHandles() *oneapiHandles {
oHandles := &oneapiHandles{}
// Short Circuit if we already know which library to use
// ignore bootstrap errors in this case since we already recorded them
if oneapiLibPath != "" {
oHandles.deviceCount, oHandles.oneapi, _, _ = loadOneapiMgmt([]string{oneapiLibPath})
return oHandles
}
oneapiLibPaths := FindGPULibs(OneapiMgmtName, OneapiGlobs)
if len(oneapiLibPaths) > 0 {
var err error
oHandles.deviceCount, oHandles.oneapi, oneapiLibPath, err = loadOneapiMgmt(oneapiLibPaths)
if err != nil {
bootstrapErrors = append(bootstrapErrors, err)
}
}
return oHandles
}
func GetCPUInfo() GpuInfoList {
gpuMutex.Lock()
if !bootstrapped {
gpuMutex.Unlock()
GetGPUInfo()
} else {
gpuMutex.Unlock()
}
return GpuInfoList{cpus[0].GpuInfo}
}
func GetGPUInfo() GpuInfoList {
// TODO - consider exploring lspci (and equivalent on windows) to check for
// GPUs so we can report warnings if we see Nvidia/AMD but fail to load the libraries
gpuMutex.Lock()
defer gpuMutex.Unlock()
needRefresh := true
var cHandles *cudaHandles
var oHandles *oneapiHandles
defer func() {
if cHandles != nil {
if cHandles.cudart != nil {
C.cudart_release(*cHandles.cudart)
}
if cHandles.nvcuda != nil {
C.nvcuda_release(*cHandles.nvcuda)
}
if cHandles.nvml != nil {
C.nvml_release(*cHandles.nvml)
}
}
if oHandles != nil {
if oHandles.oneapi != nil {
// TODO - is this needed?
C.oneapi_release(*oHandles.oneapi)
}
}
}()
if !bootstrapped {
slog.Info("looking for compatible GPUs")
bootstrapErrors = []error{}
needRefresh = false
cpuCapability = GetCPUCapability()
var memInfo C.mem_info_t
mem, err := GetCPUMem()
if err != nil {
slog.Warn("error looking up system memory", "error", err)
}
depPath := LibraryDir()
details, err := GetCPUDetails()
if err != nil {
slog.Warn("failed to lookup CPU details", "error", err)
}
cpus = []CPUInfo{
{
GpuInfo: GpuInfo{
memInfo: mem,
Library: "cpu",
Variant: cpuCapability.String(),
ID: "0",
DependencyPath: []string{depPath},
},
CPUs: details,
},
}
// Fallback to CPU mode if we're lacking required vector extensions on x86
if cpuCapability < GPURunnerCPUCapability && runtime.GOARCH == "amd64" {
err := fmt.Errorf("CPU does not have minimum vector extensions, GPU inference disabled. Required:%s Detected:%s", GPURunnerCPUCapability, cpuCapability)
slog.Warn(err.Error())
bootstrapErrors = append(bootstrapErrors, err)
bootstrapped = true
// No need to do any GPU discovery, since we can't run on them
return GpuInfoList{cpus[0].GpuInfo}
}
// Load ALL libraries
cHandles = initCudaHandles()
// NVIDIA
for i := range cHandles.deviceCount {
if cHandles.cudart != nil || cHandles.nvcuda != nil {
gpuInfo := CudaGPUInfo{
GpuInfo: GpuInfo{
Library: "cuda",
},
index: i,
}
var driverMajor int
var driverMinor int
if cHandles.cudart != nil {
C.cudart_bootstrap(*cHandles.cudart, C.int(i), &memInfo)
} else {
C.nvcuda_bootstrap(*cHandles.nvcuda, C.int(i), &memInfo)
driverMajor = int(cHandles.nvcuda.driver_major)
driverMinor = int(cHandles.nvcuda.driver_minor)
}
if memInfo.err != nil {
slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
continue
}
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
gpuInfo.computeMajor = int(memInfo.major)
gpuInfo.computeMinor = int(memInfo.minor)
gpuInfo.MinimumMemory = cudaMinimumMemory
gpuInfo.DriverMajor = driverMajor
gpuInfo.DriverMinor = driverMinor
variant := cudaVariant(gpuInfo)
if depPath != "" {
gpuInfo.DependencyPath = []string{depPath}
// Check for variant specific directory
if variant != "" {
if _, err := os.Stat(filepath.Join(depPath, "cuda_"+variant)); err == nil {
gpuInfo.DependencyPath = []string{filepath.Join(depPath, "cuda_"+variant), depPath}
}
}
}
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.Variant = variant
if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
unsupportedGPUs = append(unsupportedGPUs,
UnsupportedGPUInfo{
GpuInfo: gpuInfo.GpuInfo,
})
slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
continue
}
// query the management library as well so we can record any skew between the two
// which represents overhead on the GPU we must set aside on subsequent updates
if cHandles.nvml != nil {
uuid := C.CString(gpuInfo.ID)
defer C.free(unsafe.Pointer(uuid))
C.nvml_get_free(*cHandles.nvml, uuid, &memInfo.free, &memInfo.total, &memInfo.used)
if memInfo.err != nil {
slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
} else {
if memInfo.free != 0 && uint64(memInfo.free) > gpuInfo.FreeMemory {
gpuInfo.OSOverhead = uint64(memInfo.free) - gpuInfo.FreeMemory
slog.Info("detected OS VRAM overhead",
"id", gpuInfo.ID,
"library", gpuInfo.Library,
"compute", gpuInfo.Compute,
"driver", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor),
"name", gpuInfo.Name,
"overhead", format.HumanBytes2(gpuInfo.OSOverhead),
)
}
}
}
// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
cudaGPUs = append(cudaGPUs, gpuInfo)
}
}
// Intel
if envconfig.IntelGPU() {
oHandles = initOneAPIHandles()
if oHandles != nil && oHandles.oneapi != nil {
for d := range oHandles.oneapi.num_drivers {
if oHandles.oneapi == nil {
// shouldn't happen
slog.Warn("nil oneapi handle with driver count", "count", int(oHandles.oneapi.num_drivers))
continue
}
devCount := C.oneapi_get_device_count(*oHandles.oneapi, C.int(d))
for i := range devCount {
gpuInfo := OneapiGPUInfo{
GpuInfo: GpuInfo{
Library: "oneapi",
},
driverIndex: int(d),
gpuIndex: int(i),
}
// TODO - split bootstrapping from updating free memory
C.oneapi_check_vram(*oHandles.oneapi, C.int(d), i, &memInfo)
// TODO - convert this to MinimumMemory based on testing...
var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
memInfo.free = C.uint64_t(totalFreeMem)
gpuInfo.TotalMemory = uint64(memInfo.total)
gpuInfo.FreeMemory = uint64(memInfo.free)
gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
gpuInfo.DependencyPath = []string{depPath}
oneapiGPUs = append(oneapiGPUs, gpuInfo)
}
}
}
}
rocmGPUs, err = AMDGetGPUInfo()
if err != nil {
bootstrapErrors = append(bootstrapErrors, err)
}
bootstrapped = true
if len(cudaGPUs) == 0 && len(rocmGPUs) == 0 && len(oneapiGPUs) == 0 {
slog.Info("no compatible GPUs were discovered")
}
}
// For detected GPUs, load library if not loaded
// Refresh free memory usage
if needRefresh {
mem, err := GetCPUMem()
if err != nil {
slog.Warn("error looking up system memory", "error", err)
} else {
slog.Debug("updating system memory data",
slog.Group(
"before",
"total", format.HumanBytes2(cpus[0].TotalMemory),
"free", format.HumanBytes2(cpus[0].FreeMemory),
"free_swap", format.HumanBytes2(cpus[0].FreeSwap),
),
slog.Group(
"now",
"total", format.HumanBytes2(mem.TotalMemory),
"free", format.HumanBytes2(mem.FreeMemory),
"free_swap", format.HumanBytes2(mem.FreeSwap),
),
)
cpus[0].FreeMemory = mem.FreeMemory
cpus[0].FreeSwap = mem.FreeSwap
}
var memInfo C.mem_info_t
if cHandles == nil && len(cudaGPUs) > 0 {
cHandles = initCudaHandles()
}
for i, gpu := range cudaGPUs {
if cHandles.nvml != nil {
uuid := C.CString(gpu.ID)
defer C.free(unsafe.Pointer(uuid))
C.nvml_get_free(*cHandles.nvml, uuid, &memInfo.free, &memInfo.total, &memInfo.used)
} else if cHandles.cudart != nil {
C.cudart_bootstrap(*cHandles.cudart, C.int(gpu.index), &memInfo)
} else if cHandles.nvcuda != nil {
C.nvcuda_get_free(*cHandles.nvcuda, C.int(gpu.index), &memInfo.free, &memInfo.total)
memInfo.used = memInfo.total - memInfo.free
} else {
// shouldn't happen
slog.Warn("no valid cuda library loaded to refresh vram usage")
break
}
if memInfo.err != nil {
slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
continue
}
if memInfo.free == 0 {
slog.Warn("error looking up nvidia GPU memory")
continue
}
if cHandles.nvml != nil && gpu.OSOverhead > 0 {
// When using the management library update based on recorded overhead
memInfo.free -= C.uint64_t(gpu.OSOverhead)
}
slog.Debug("updating cuda memory data",
"gpu", gpu.ID,
"name", gpu.Name,
"overhead", format.HumanBytes2(gpu.OSOverhead),
slog.Group(
"before",
"total", format.HumanBytes2(gpu.TotalMemory),
"free", format.HumanBytes2(gpu.FreeMemory),
),
slog.Group(
"now",
"total", format.HumanBytes2(uint64(memInfo.total)),
"free", format.HumanBytes2(uint64(memInfo.free)),
"used", format.HumanBytes2(uint64(memInfo.used)),
),
)
cudaGPUs[i].FreeMemory = uint64(memInfo.free)
}
if oHandles == nil && len(oneapiGPUs) > 0 {
oHandles = initOneAPIHandles()
}
for i, gpu := range oneapiGPUs {
if oHandles.oneapi == nil {
// shouldn't happen
slog.Warn("nil oneapi handle with device count", "count", oHandles.deviceCount)
continue
}
C.oneapi_check_vram(*oHandles.oneapi, C.int(gpu.driverIndex), C.int(gpu.gpuIndex), &memInfo)
// TODO - convert this to MinimumMemory based on testing...
var totalFreeMem float64 = float64(memInfo.free) * 0.95 // work-around: leave some reserve vram for mkl lib used in ggml-sycl backend.
memInfo.free = C.uint64_t(totalFreeMem)
oneapiGPUs[i].FreeMemory = uint64(memInfo.free)
}
err = RocmGPUInfoList(rocmGPUs).RefreshFreeMemory()
if err != nil {
slog.Debug("problem refreshing ROCm free memory", "error", err)
}
}
resp := []GpuInfo{}
for _, gpu := range cudaGPUs {
resp = append(resp, gpu.GpuInfo)
}
for _, gpu := range rocmGPUs {
resp = append(resp, gpu.GpuInfo)
}
for _, gpu := range oneapiGPUs {
resp = append(resp, gpu.GpuInfo)
}
if len(resp) == 0 {
resp = append(resp, cpus[0].GpuInfo)
}
return resp
}
func FindGPULibs(baseLibName string, defaultPatterns []string) []string {
// Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them
var ldPaths []string
gpuLibPaths := []string{}
slog.Debug("Searching for GPU library", "name", baseLibName)
// Start with our bundled libraries
patterns := []string{filepath.Join(LibraryDir(), baseLibName)}
switch runtime.GOOS {
case "windows":
ldPaths = strings.Split(os.Getenv("PATH"), ";")
case "linux":
ldPaths = strings.Split(os.Getenv("LD_LIBRARY_PATH"), ":")
default:
return gpuLibPaths
}
// Then with whatever we find in the PATH/LD_LIBRARY_PATH
for _, ldPath := range ldPaths {
d, err := filepath.Abs(ldPath)
if err != nil {
continue
}
patterns = append(patterns, filepath.Join(d, baseLibName))
}
patterns = append(patterns, defaultPatterns...)
slog.Debug("gpu library search", "globs", patterns)
for _, pattern := range patterns {
// Nvidia PhysX known to return bogus results
if strings.Contains(pattern, "PhysX") {
slog.Debug("skipping PhysX cuda library path", "path", pattern)
continue
}
// Ignore glob discovery errors
matches, _ := filepath.Glob(pattern)
for _, match := range matches {
// Resolve any links so we don't try the same lib multiple times
// and weed out any dups across globs
libPath := match
tmp := match
var err error
for ; err == nil; tmp, err = os.Readlink(libPath) {
if !filepath.IsAbs(tmp) {
tmp = filepath.Join(filepath.Dir(libPath), tmp)
}
libPath = tmp
}
new := true
for _, cmp := range gpuLibPaths {
if cmp == libPath {
new = false
break
}
}
if new {
gpuLibPaths = append(gpuLibPaths, libPath)
}
}
}
slog.Debug("discovered GPU libraries", "paths", gpuLibPaths)
return gpuLibPaths
}
// Bootstrap the runtime library
// Returns: num devices, handle, libPath, error
func loadCUDARTMgmt(cudartLibPaths []string) (int, *C.cudart_handle_t, string, error) {
var resp C.cudart_init_resp_t
resp.ch.verbose = getVerboseState()
var err error
for _, libPath := range cudartLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.cudart_init(lib, &resp)
if resp.err != nil {
err = fmt.Errorf("Unable to load cudart library %s: %s", libPath, C.GoString(resp.err))
slog.Debug(err.Error())
C.free(unsafe.Pointer(resp.err))
} else {
err = nil
return int(resp.num_devices), &resp.ch, libPath, err
}
}
return 0, nil, "", err
}
// Bootstrap the driver library
// Returns: num devices, handle, libPath, error
func loadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string, error) {
var resp C.nvcuda_init_resp_t
resp.ch.verbose = getVerboseState()
var err error
for _, libPath := range nvcudaLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.nvcuda_init(lib, &resp)
if resp.err != nil {
// Decide what log level based on the type of error message to help users understand why
switch resp.cudaErr {
case C.CUDA_ERROR_INSUFFICIENT_DRIVER, C.CUDA_ERROR_SYSTEM_DRIVER_MISMATCH:
err = fmt.Errorf("version mismatch between driver and cuda driver library - reboot or upgrade may be required: library %s", libPath)
slog.Warn(err.Error())
case C.CUDA_ERROR_NO_DEVICE:
err = fmt.Errorf("no nvidia devices detected by library %s", libPath)
slog.Info(err.Error())
case C.CUDA_ERROR_UNKNOWN:
err = fmt.Errorf("unknown error initializing cuda driver library %s: %s. see https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for more information", libPath, C.GoString(resp.err))
slog.Warn(err.Error())
default:
msg := C.GoString(resp.err)
if strings.Contains(msg, "wrong ELF class") {
slog.Debug("skipping 32bit library", "library", libPath)
} else {
err = fmt.Errorf("Unable to load cudart library %s: %s", libPath, C.GoString(resp.err))
slog.Info(err.Error())
}
}
C.free(unsafe.Pointer(resp.err))
} else {
err = nil
return int(resp.num_devices), &resp.ch, libPath, err
}
}
return 0, nil, "", err
}
// Bootstrap the management library
// Returns: handle, libPath, error
func loadNVMLMgmt(nvmlLibPaths []string) (*C.nvml_handle_t, string, error) {
var resp C.nvml_init_resp_t
resp.ch.verbose = getVerboseState()
var err error
for _, libPath := range nvmlLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.nvml_init(lib, &resp)
if resp.err != nil {
err = fmt.Errorf("Unable to load NVML management library %s: %s", libPath, C.GoString(resp.err))
slog.Info(err.Error())
C.free(unsafe.Pointer(resp.err))
} else {
err = nil
return &resp.ch, libPath, err
}
}
return nil, "", err
}
// bootstrap the Intel GPU library
// Returns: num devices, handle, libPath, error
func loadOneapiMgmt(oneapiLibPaths []string) (int, *C.oneapi_handle_t, string, error) {
var resp C.oneapi_init_resp_t
num_devices := 0
resp.oh.verbose = getVerboseState()
var err error
for _, libPath := range oneapiLibPaths {
lib := C.CString(libPath)
defer C.free(unsafe.Pointer(lib))
C.oneapi_init(lib, &resp)
if resp.err != nil {
err = fmt.Errorf("Unable to load oneAPI management library %s: %s", libPath, C.GoString(resp.err))
slog.Debug(err.Error())
C.free(unsafe.Pointer(resp.err))
} else {
err = nil
for i := range resp.oh.num_drivers {
num_devices += int(C.oneapi_get_device_count(resp.oh, C.int(i)))
}
return num_devices, &resp.oh, libPath, err
}
}
return 0, nil, "", err
}
func getVerboseState() C.uint16_t {
if envconfig.Debug() {
return C.uint16_t(1)
}
return C.uint16_t(0)
}
// Given the list of GPUs this instantiation is targeted for,
// figure out the visible devices environment variable
//
// If different libraries are detected, the first one is what we use
func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
if len(l) == 0 {
return "", ""
}
switch l[0].Library {
case "cuda":
return cudaGetVisibleDevicesEnv(l)
case "rocm":
return rocmGetVisibleDevicesEnv(l)
case "oneapi":
return oneapiGetVisibleDevicesEnv(l)
default:
slog.Debug("no filter required for library " + l[0].Library)
return "", ""
}
}
func LibraryDir() string {
// On Windows/linux we bundle the dependencies at the same level as the executable
appExe, err := os.Executable()
if err != nil {
slog.Warn("failed to lookup executable path", "error", err)
}
cwd, err := os.Getwd()
if err != nil {
slog.Warn("failed to lookup working directory", "error", err)
}
// Scan for any of our dependeices, and pick first match
for _, root := range []string{filepath.Dir(appExe), filepath.Join(filepath.Dir(appExe), envconfig.LibRelativeToExe()), cwd} {
libDep := filepath.Join("lib", "ollama")
if _, err := os.Stat(filepath.Join(root, libDep)); err == nil {
return filepath.Join(root, libDep)
}
// Developer mode, local build
if _, err := os.Stat(filepath.Join(root, runtime.GOOS+"-"+runtime.GOARCH, libDep)); err == nil {
return filepath.Join(root, runtime.GOOS+"-"+runtime.GOARCH, libDep)
}
if _, err := os.Stat(filepath.Join(root, "dist", runtime.GOOS+"-"+runtime.GOARCH, libDep)); err == nil {
return filepath.Join(root, "dist", runtime.GOOS+"-"+runtime.GOARCH, libDep)
}
}
slog.Warn("unable to locate gpu dependency libraries")
return ""
}
func GetSystemInfo() SystemInfo {
gpus := GetGPUInfo()
gpuMutex.Lock()
defer gpuMutex.Unlock()
discoveryErrors := []string{}
for _, err := range bootstrapErrors {
discoveryErrors = append(discoveryErrors, err.Error())
}
if len(gpus) == 1 && gpus[0].Library == "cpu" {
gpus = []GpuInfo{}
}
return SystemInfo{
System: cpus[0],
GPUs: gpus,
UnsupportedGPUs: unsupportedGPUs,
DiscoveryErrors: discoveryErrors,
}
}

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@ -1,101 +0,0 @@
//go:build darwin
package discover
/*
#cgo CFLAGS: -x objective-c
#cgo LDFLAGS: -framework Foundation -framework CoreGraphics -framework Metal
#include "gpu_info_darwin.h"
*/
import "C"
import (
"log/slog"
"runtime"
"syscall"
"github.com/ollama/ollama/format"
)
const (
metalMinimumMemory = 512 * format.MebiByte
)
func GetGPUInfo() GpuInfoList {
mem, _ := GetCPUMem()
if runtime.GOARCH == "amd64" {
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability().String(),
memInfo: mem,
},
}
}
info := GpuInfo{
Library: "metal",
ID: "0",
}
info.TotalMemory = uint64(C.getRecommendedMaxVRAM())
// TODO is there a way to gather actual allocated video memory? (currentAllocatedSize doesn't work)
info.FreeMemory = info.TotalMemory
info.MinimumMemory = metalMinimumMemory
return []GpuInfo{info}
}
func GetCPUInfo() GpuInfoList {
mem, _ := GetCPUMem()
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability().String(),
memInfo: mem,
},
}
}
func GetCPUMem() (memInfo, error) {
return memInfo{
TotalMemory: uint64(C.getPhysicalMemory()),
FreeMemory: uint64(C.getFreeMemory()),
// FreeSwap omitted as Darwin uses dynamic paging
}, nil
}
func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
// No-op on darwin
return "", ""
}
func GetSystemInfo() SystemInfo {
mem, _ := GetCPUMem()
query := "hw.perflevel0.physicalcpu"
perfCores, err := syscall.SysctlUint32(query)
if err != nil {
slog.Warn("failed to discover physical CPU details", "query", query, "error", err)
}
query = "hw.perflevel1.physicalcpu"
efficiencyCores, _ := syscall.SysctlUint32(query) // On x86 xeon this wont return data
// Determine thread count
query = "hw.logicalcpu"
logicalCores, _ := syscall.SysctlUint32(query)
return SystemInfo{
System: CPUInfo{
GpuInfo: GpuInfo{
memInfo: mem,
},
CPUs: []CPU{
{
CoreCount: int(perfCores + efficiencyCores),
EfficiencyCoreCount: int(efficiencyCores),
ThreadCount: int(logicalCores),
},
},
},
GPUs: GetGPUInfo(),
}
}

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@ -1,35 +0,0 @@
#import <Foundation/Foundation.h>
#import <mach/mach.h>
#include "gpu_info_darwin.h"
uint64_t getRecommendedMaxVRAM() {
id<MTLDevice> device = MTLCreateSystemDefaultDevice();
uint64_t result = device.recommendedMaxWorkingSetSize;
CFRelease(device);
return result;
}
// getPhysicalMemory returns the total physical memory in bytes
uint64_t getPhysicalMemory() {
return [NSProcessInfo processInfo].physicalMemory;
}
// getFreeMemory returns the total free memory in bytes, including inactive
// memory that can be reclaimed by the system.
uint64_t getFreeMemory() {
mach_port_t host_port = mach_host_self();
mach_msg_type_number_t host_size = sizeof(vm_statistics64_data_t) / sizeof(integer_t);
vm_size_t pagesize;
vm_statistics64_data_t vm_stat;
host_page_size(host_port, &pagesize);
if (host_statistics64(host_port, HOST_VM_INFO64, (host_info64_t)&vm_stat, &host_size) != KERN_SUCCESS) {
return 0;
}
uint64_t free_memory = (uint64_t)vm_stat.free_count * pagesize;
free_memory += (uint64_t)vm_stat.speculative_count * pagesize;
free_memory += (uint64_t)vm_stat.inactive_count * pagesize;
return free_memory;
}

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@ -1,104 +0,0 @@
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include <string.h>
#include "gpu_info_nvml.h"
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
nvmlReturn_t ret;
resp->err = NULL;
const int buflen = 256;
char buf[buflen + 1];
int i;
struct lookup {
char *s;
void **p;
} l[] = {
{"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
{"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
{"nvmlDeviceGetHandleByUUID", (void *)&resp->ch.nvmlDeviceGetHandleByUUID},
{"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(nvml_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", nvml_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
nvml_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", nvml_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
resp->ch.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
ret = (*resp->ch.nvmlInit_v2)();
if (ret != NVML_SUCCESS) {
LOG(resp->ch.verbose, "nvmlInit_v2 err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "nvml vram init failure: %d", ret);
resp->err = strdup(buf);
return;
}
}
void nvml_get_free(nvml_handle_t h, char *uuid, uint64_t *free, uint64_t *total, uint64_t *used) {
nvmlDevice_t device;
nvmlMemory_t memInfo = {0};
nvmlReturn_t ret;
ret = (*h.nvmlDeviceGetHandleByUUID)((const char *)(uuid), &device);
if (ret != NVML_SUCCESS) {
LOG(1, "unable to get device handle %s: %d", uuid, ret);
*free = 0;
return;
}
ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
if (ret != NVML_SUCCESS) {
LOG(1, "device memory info lookup failure %s: %d", uuid, ret);
*free = 0;
return;
}
*free = memInfo.free;
*total = memInfo.total;
*used = memInfo.used;
}
void nvml_release(nvml_handle_t h) {
LOG(h.verbose, "releasing nvml library\n");
nvmlReturn_t ret;
ret = (*h.nvmlShutdown)();
if (ret != NVML_SUCCESS) {
LOG(1, "error during nvmlShutdown %d", ret);
}
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
#endif // __APPLE__

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@ -1,48 +0,0 @@
#ifndef __APPLE__
#ifndef __GPU_INFO_NVML_H__
#define __GPU_INFO_NVML_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum nvmlReturn_enum {
NVML_SUCCESS = 0,
// Other values omitted for now...
} nvmlReturn_t;
typedef void *nvmlDevice_t; // Opaque is sufficient
typedef struct nvmlMemory_st {
unsigned long long total;
unsigned long long free;
unsigned long long used;
} nvmlMemory_t;
typedef enum nvmlBrandType_enum
{
NVML_BRAND_UNKNOWN = 0,
} nvmlBrandType_t;
typedef struct nvml_handle {
void *handle;
uint16_t verbose;
nvmlReturn_t (*nvmlInit_v2)(void);
nvmlReturn_t (*nvmlShutdown)(void);
nvmlReturn_t (*nvmlDeviceGetHandleByUUID)(const char *, nvmlDevice_t *);
nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
} nvml_handle_t;
typedef struct nvml_init_resp {
char *err; // If err is non-null handle is invalid
nvml_handle_t ch;
} nvml_init_resp_t;
typedef struct nvml_compute_capability {
char *err;
int major;
int minor;
} nvml_compute_capability_t;
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp);
void nvml_get_free(nvml_handle_t ch, char *uuid, uint64_t *free, uint64_t *total, uint64_t *used);
void nvml_release(nvml_handle_t ch);
#endif // __GPU_INFO_NVML_H__
#endif // __APPLE__

View File

@ -1,259 +0,0 @@
#ifndef __APPLE__
#include "gpu_info_oneapi.h"
#include <string.h>
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
ze_result_t ret;
resp->err = NULL;
resp->oh.devices = NULL;
resp->oh.num_devices = NULL;
resp->oh.drivers = NULL;
resp->oh.num_drivers = 0;
const int buflen = 256;
char buf[buflen + 1];
int i, d;
struct lookup {
char *s;
void **p;
} l[] = {
{"zesInit", (void *)&resp->oh.zesInit},
{"zesDriverGet", (void *)&resp->oh.zesDriverGet},
{"zesDeviceGet", (void *)&resp->oh.zesDeviceGet},
{"zesDeviceGetProperties", (void *)&resp->oh.zesDeviceGetProperties},
{"zesDeviceEnumMemoryModules",
(void *)&resp->oh.zesDeviceEnumMemoryModules},
{"zesMemoryGetProperties", (void *)&resp->oh.zesMemoryGetProperties},
{"zesMemoryGetState", (void *)&resp->oh.zesMemoryGetState},
{NULL, NULL},
};
resp->oh.handle = LOAD_LIBRARY(oneapi_lib_path, RTLD_LAZY);
if (!resp->oh.handle) {
char *msg = LOAD_ERR();
snprintf(buf, buflen,
"Unable to load %s library to query for Intel GPUs: %s\n",
oneapi_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->oh.verbose,
"wiring Level-Zero management library functions in %s\n",
oneapi_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->oh.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->oh.handle, l[i].s);
if (!*(l[i].p)) {
resp->oh.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->oh.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->oh.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s, msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
LOG(resp->oh.verbose, "calling zesInit\n");
ret = (*resp->oh.zesInit)(0);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesInit err: %x\n", ret);
snprintf(buf, buflen, "oneapi vram init failure: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "calling zesDriverGet\n");
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "oneapi driver count: %d\n", resp->oh.num_drivers);
resp->oh.drivers = malloc(resp->oh.num_drivers * sizeof(zes_driver_handle_t));
resp->oh.num_devices = malloc(resp->oh.num_drivers * sizeof(uint32_t));
memset(&resp->oh.num_devices[0], 0, resp->oh.num_drivers * sizeof(uint32_t));
resp->oh.devices =
malloc(resp->oh.num_drivers * sizeof(zes_device_handle_t *));
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, &resp->oh.drivers[0]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
for (d = 0; d < resp->oh.num_drivers; d++) {
LOG(resp->oh.verbose, "calling zesDeviceGet count %d: %p\n", d, resp->oh.drivers[d]);
ret = (*resp->oh.zesDeviceGet)(resp->oh.drivers[d],
&resp->oh.num_devices[d], NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
resp->oh.devices[d] =
malloc(resp->oh.num_devices[d] * sizeof(zes_device_handle_t));
ret = (*resp->oh.zesDeviceGet)(
resp->oh.drivers[d], &resp->oh.num_devices[d], resp->oh.devices[d]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
}
return;
}
void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
mem_info_t *resp) {
ze_result_t ret;
resp->err = NULL;
uint64_t totalMem = 0;
uint64_t usedMem = 0;
const int buflen = 256;
char buf[buflen + 1];
int i, d, m;
if (h.handle == NULL) {
resp->err = strdup("Level-Zero handle not initialized");
return;
}
if (driver > h.num_drivers || device > h.num_devices[driver]) {
resp->err = strdup("driver of device index out of bounds");
return;
}
resp->total = 0;
resp->free = 0;
zes_device_ext_properties_t ext_props;
ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
ext_props.pNext = NULL;
zes_device_properties_t props;
props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
props.pNext = &ext_props;
ret = (*h.zesDeviceGetProperties)(h.devices[driver][device], &props);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get device properties: %d", ret);
resp->err = strdup(buf);
return;
}
snprintf(&resp->gpu_name[0], GPU_NAME_LEN, "%s", props.modelName);
// TODO this needs to map to ONEAPI_DEVICE_SELECTOR syntax
// (this is probably wrong...)
// TODO - the driver isn't included - what if there are multiple drivers?
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", device);
if (h.verbose) {
// When in verbose mode, report more information about
// the card we discover.
LOG(h.verbose, "[%d:%d] oneAPI device name: %s\n", driver, device,
props.modelName);
LOG(h.verbose, "[%d:%d] oneAPI brand: %s\n", driver, device,
props.brandName);
LOG(h.verbose, "[%d:%d] oneAPI vendor: %s\n", driver, device,
props.vendorName);
LOG(h.verbose, "[%d:%d] oneAPI S/N: %s\n", driver, device,
props.serialNumber);
LOG(h.verbose, "[%d:%d] oneAPI board number: %s\n", driver, device,
props.boardNumber);
}
// TODO
// Compute Capability equivalent in resp->major, resp->minor, resp->patch
uint32_t memCount = 0;
ret = (*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount,
NULL);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to enumerate Level-Zero memory modules: %x",
ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
(*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount, mems);
for (m = 0; m < memCount; m++) {
zes_mem_state_t state;
state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
state.pNext = NULL;
ret = (*h.zesMemoryGetState)(mems[m], &state);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get memory state: %x", ret);
resp->err = strdup(buf);
free(mems);
return;
}
resp->total += state.size;
resp->free += state.free;
}
free(mems);
}
void oneapi_release(oneapi_handle_t h) {
int d;
LOG(h.verbose, "releasing oneapi library\n");
for (d = 0; d < h.num_drivers; d++) {
if (h.devices != NULL && h.devices[d] != NULL) {
free(h.devices[d]);
}
}
if (h.devices != NULL) {
free(h.devices);
h.devices = NULL;
}
if (h.num_devices != NULL) {
free(h.num_devices);
h.num_devices = NULL;
}
if (h.drivers != NULL) {
free(h.drivers);
h.drivers = NULL;
}
h.num_drivers = 0;
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
int oneapi_get_device_count(oneapi_handle_t h, int driver) {
if (h.handle == NULL || h.num_devices == NULL) {
return 0;
}
if (driver > h.num_drivers) {
return 0;
}
return (int)h.num_devices[driver];
}
#endif // __APPLE__

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@ -1,199 +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
}
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
for _, tc := range threadsByCoreBySocket[id] {
s.ThreadCount += tc
}
// This only works if HT is enabled, consider a more reliable model, maybe cache size comparisons?
efficiencyCoreCount := 0
for _, threads := range threadsByCoreBySocket[id] {
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
}

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@ -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

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@ -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++
}
}
}
}
}
// Sumarize 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
}

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