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4 Commits
main ... native

Author SHA1 Message Date
jmorganca
201a987ff9 some more menu options... 2024-04-28 12:40:52 -04:00
jmorganca
2d8125042a Touch ID for cli install; server restarts 2024-04-27 22:42:38 -04:00
jmorganca
776e7bb5e4 app: fix status item icons 2024-04-27 15:57:57 -04:00
jmorganca
b8d7ca1a7b Native implementation of macOS app 2024-04-27 14:20:10 -04:00
729 changed files with 23971 additions and 196994 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
@ -32,7 +28,6 @@ jobs:
security unlock-keychain -p password build.keychain
security import certificate.p12 -k build.keychain -P $MACOS_SIGNING_KEY_PASSWORD -T /usr/bin/codesign
security set-key-partition-list -S apple-tool:,apple:,codesign: -s -k password build.keychain
security set-keychain-settings -lut 3600 build.keychain
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
@ -43,8 +38,8 @@ 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 +47,8 @@ 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 +59,14 @@ 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 +91,180 @@ 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 +272,6 @@ jobs:
- generate-windows-cuda
- generate-windows-rocm
- generate-windows-cpu
- windows-arm64
env:
KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
steps:
@ -424,24 +303,6 @@ jobs:
write-host "Installing plugin"
& "${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 +313,24 @@ 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"
$env:ARCH="amd64"
if (!(gcc --version | select-string -quiet clang)) { throw "wrong gcc compiler detected - must be clang" }
& .\scripts\build_windows.ps1
- uses: actions/upload-artifact@v4
with:
@ -483,7 +344,9 @@ jobs:
environment: release
runs-on: linux
env:
PLATFORM: linux/amd64
OLLAMA_SKIP_MANIFEST_CREATE: '1'
BUILD_ARCH: amd64
PUSH: '1'
steps:
- uses: actions/checkout@v4
with:
@ -491,8 +354,15 @@ jobs:
- name: Set Version
shell: bash
run: echo "VERSION=${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 +376,9 @@ 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 +407,14 @@ 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 +422,6 @@ 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 +434,8 @@ jobs:
permissions:
contents: write
env:
GH_TOKEN: ${{ github.token }}
OLLAMA_SKIP_IMAGE_BUILD: '1'
PUSH: '1'
steps:
- uses: actions/checkout@v4
- name: Set Version
@ -736,6 +443,12 @@ jobs:
run: |
echo "VERSION=${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 +457,17 @@ 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:
@ -38,171 +34,18 @@ jobs:
git diff-tree -r --no-commit-id --name-only \
$(git merge-base ${{ github.event.pull_request.base.sha }} ${{ github.event.pull_request.head.sha }}) \
${{ github.event.pull_request.head.sha }} \
| xargs python3 -c "import sys; from pathlib import Path; print(any(Path(x).match(glob) for x in sys.argv[1:] for glob in '$*'.split(' ')))"
| xargs python3 -c "import sys; print(any([x.startswith('$1') for x in sys.argv[1:]]))"
}
{
echo RUNNERS=$(changed 'llama/**')
echo GENERATE=$(changed llm/)
echo GENERATE_CUDA=$(changed llm/)
echo GENERATE_ROCM=$(changed llm/)
} >>$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 +286,7 @@ jobs:
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
OLLAMA_CPU_TARGET: 'static'
steps:
- uses: actions/checkout@v4
with:
@ -306,21 +297,23 @@ 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

6
.gitignore vendored
View File

@ -5,14 +5,10 @@
.swp
dist
ollama
ggml-metal.metal
.cache
*.exe
.idea
test_data
*.crt
llm/build
build/*/*/*
!build/**/placeholder
llama/build
__debug_bin*
llama/vendor

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 $@

212
README.md
View File

@ -1,18 +1,18 @@
<div align="center">
 <img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
<img alt="ollama" height="200px" src="https://github.com/ollama/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
</div>
# Ollama
[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
Get up and running with large language models.
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 +47,22 @@ 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 | 3,8B | 2.3GB | `ollama run phi3` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| 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` |
| Gemma | 2B | 1.4GB | `ollama run gemma:2b` |
| Gemma | 7B | 4.8GB | `ollama run gemma:7b` |
| 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 +94,16 @@ 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 +138,7 @@ 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 +146,13 @@ 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
@ -178,48 +169,48 @@ 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
### Pass in prompt as arguments
```
$ 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.
## Building
See the [developer guide](https://github.com/ollama/ollama/blob/main/docs/development.md)
Install `cmake` and `go`:
```
brew install cmake go
```
Then generate dependencies:
```
go generate ./...
```
Then build the binary:
```
go build .
```
More detailed instructions can be found in the [developer guide](https://github.com/ollama/ollama/blob/main/docs/development.md)
### Running local builds
@ -232,7 +223,7 @@ Next, start the server:
Finally, in a separate shell, run a model:
```
./ollama run llama3.2
./ollama run llama3
```
## REST API
@ -243,7 +234,7 @@ 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 +243,7 @@ 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?" }
]
@ -267,7 +258,6 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Open WebUI](https://github.com/open-webui/open-webui)
- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
- [Hollama](https://github.com/fmaclen/hollama)
- [Lollms-Webui](https://github.com/ParisNeo/lollms-webui)
- [LibreChat](https://github.com/danny-avila/LibreChat)
- [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
@ -294,47 +284,17 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [OllamaGUI](https://github.com/enoch1118/ollamaGUI)
- [OpenAOE](https://github.com/InternLM/OpenAOE)
- [Odin Runes](https://github.com/leonid20000/OdinRunes)
- [LLM-X](https://github.com/mrdjohnson/llm-x) (Progressive Web App)
- [LLM-X: Progressive Web App](https://github.com/mrdjohnson/llm-x)
- [AnythingLLM (Docker + MacOs/Windows/Linux native app)](https://github.com/Mintplex-Labs/anything-llm)
- [Ollama Basic Chat: Uses HyperDiv Reactive UI](https://github.com/rapidarchitect/ollama_basic_chat)
- [Ollama-chats RPG](https://github.com/drazdra/ollama-chats)
- [QA-Pilot](https://github.com/reid41/QA-Pilot) (Chat with Code Repository)
- [ChatOllama](https://github.com/sugarforever/chat-ollama) (Open Source Chatbot based on Ollama with Knowledge Bases)
- [CRAG Ollama Chat](https://github.com/Nagi-ovo/CRAG-Ollama-Chat) (Simple Web Search with Corrective RAG)
- [RAGFlow](https://github.com/infiniflow/ragflow) (Open-source Retrieval-Augmented Generation engine based on deep document understanding)
- [StreamDeploy](https://github.com/StreamDeploy-DevRel/streamdeploy-llm-app-scaffold) (LLM Application Scaffold)
- [chat](https://github.com/swuecho/chat) (chat web app for teams)
- [QA-Pilot: Chat with Code Repository](https://github.com/reid41/QA-Pilot)
- [ChatOllama: Open Source Chatbot based on Ollama with Knowledge Bases](https://github.com/sugarforever/chat-ollama)
- [CRAG Ollama Chat: Simple Web Search with Corrective RAG](https://github.com/Nagi-ovo/CRAG-Ollama-Chat)
- [RAGFlow: Open-source Retrieval-Augmented Generation engine based on deep document understanding](https://github.com/infiniflow/ragflow)
- [chat: chat web app for teams](https://github.com/swuecho/chat)
- [Lobe Chat](https://github.com/lobehub/lobe-chat) with [Integrating Doc](https://lobehub.com/docs/self-hosting/examples/ollama)
- [Ollama RAG Chatbot](https://github.com/datvodinh/rag-chatbot.git) (Local Chat with multiple PDFs using Ollama and RAG)
- [BrainSoup](https://www.nurgo-software.com/products/brainsoup) (Flexible native client with RAG & multi-agent automation)
- [macai](https://github.com/Renset/macai) (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
- [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)
- [Ollama RAG Chatbot: Local Chat with multiples PDFs using Ollama and RAG.](https://github.com/datvodinh/rag-chatbot.git)
### Terminal
@ -357,14 +317,6 @@ 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 +326,19 @@ 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)
@ -405,27 +348,14 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Haystack](https://github.com/deepset-ai/haystack-integrations/blob/main/integrations/ollama.md)
- [Elixir LangChain](https://github.com/brainlid/langchain)
- [Ollama for R - rollama](https://github.com/JBGruber/rollama)
- [Ollama for R - ollama-r](https://github.com/hauselin/ollama-r)
- [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex)
- [Ollama Connector for SAP ABAP](https://github.com/b-tocs/abap_btocs_ollama)
- [Testcontainers](https://testcontainers.com/modules/ollama/)
- [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
@ -440,30 +370,18 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Ollama Telegram Bot](https://github.com/ruecat/ollama-telegram)
- [Hass Ollama Conversation](https://github.com/ej52/hass-ollama-conversation)
- [Rivet plugin](https://github.com/abrenneke/rivet-plugin-ollama)
- [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
- [Obsidian BMO Chatbot plugin](https://github.com/longy2k/obsidian-bmo-chatbot)
- [Cliobot](https://github.com/herval/cliobot) (Telegram bot with Ollama support)
- [Copilot for Obsidian plugin](https://github.com/logancyang/obsidian-copilot)
- [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
- [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
- [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
- [Ollama Copilot](https://github.com/bernardo-bruning/ollama-copilot) (Proxy that allows you to use ollama as a copilot like Github copilot)
- [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
- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.
### 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

@ -1,16 +1,9 @@
// Package api implements the client-side API for code wishing to interact
// with the ollama service. The methods of the [Client] type correspond to
// the ollama REST API as described in [the API documentation].
// the ollama REST API as described in https://github.com/ollama/ollama/blob/main/docs/api.md
//
// The ollama command-line client itself uses this package to interact with
// the backend service.
//
// # Examples
//
// Several examples of using this package are available [in the GitHub
// repository].
//
// [the API documentation]: https://github.com/ollama/ollama/blob/main/docs/api.md
// [in the GitHub repository]: https://github.com/ollama/ollama/tree/main/examples
package api
import (
@ -18,14 +11,15 @@ import (
"bytes"
"context"
"encoding/json"
"errors"
"fmt"
"io"
"net"
"net/http"
"net/url"
"os"
"runtime"
"strings"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/version"
)
@ -55,7 +49,7 @@ func checkError(resp *http.Response, body []byte) error {
// ClientFromEnvironment creates a new [Client] using configuration from the
// environment variable OLLAMA_HOST, which points to the network host and
// port on which the ollama service is listening. The format of this variable
// port on which the ollama service is listenting. The format of this variable
// is:
//
// <scheme>://<host>:<port>
@ -63,8 +57,36 @@ 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) {
defaultPort := "11434"
scheme, hostport, ok := strings.Cut(os.Getenv("OLLAMA_HOST"), "://")
switch {
case !ok:
scheme, hostport = "http", os.Getenv("OLLAMA_HOST")
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
}
}
return &Client{
base: envconfig.Host(),
base: &url.URL{
Scheme: scheme,
Host: net.JoinHostPort(host, port),
},
http: http.DefaultClient,
}, nil
}
@ -173,7 +195,7 @@ 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 {
@ -250,14 +272,8 @@ func (c *Client) Pull(ctx context.Context, req *PullRequest, fn PullProgressFunc
})
}
// PushProgressFunc is a function that [Client.Push] invokes when progress is
// made.
// It's similar to other progress function types like [PullProgressFunc].
type PushProgressFunc func(ProgressResponse) error
// Push uploads a model to the model library; requires registering for ollama.ai
// and adding a public key first. fn is called each time progress is made on
// the request and can be used to display a progress bar, etc.
func (c *Client) Push(ctx context.Context, req *PushRequest, fn PushProgressFunc) error {
return c.stream(ctx, http.MethodPost, "/api/push", req, func(bts []byte) error {
var resp ProgressResponse
@ -269,15 +285,8 @@ func (c *Client) Push(ctx context.Context, req *PushRequest, fn PushProgressFunc
})
}
// CreateProgressFunc is a function that [Client.Create] invokes when progress
// is made.
// It's similar to other progress function types like [PullProgressFunc].
type CreateProgressFunc func(ProgressResponse) error
// Create creates a model from a [Modelfile]. fn is a progress function that
// behaves similarly to other methods (see [Client.Pull]).
//
// [Modelfile]: https://github.com/ollama/ollama/blob/main/docs/modelfile.md
func (c *Client) Create(ctx context.Context, req *CreateRequest, fn CreateProgressFunc) error {
return c.stream(ctx, http.MethodPost, "/api/create", req, func(bts []byte) error {
var resp ProgressResponse
@ -289,7 +298,6 @@ func (c *Client) Create(ctx context.Context, req *CreateRequest, fn CreateProgre
})
}
// List lists models that are available locally.
func (c *Client) List(ctx context.Context) (*ListResponse, error) {
var lr ListResponse
if err := c.do(ctx, http.MethodGet, "/api/tags", nil, &lr); err != nil {
@ -298,17 +306,6 @@ 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
if err := c.do(ctx, http.MethodGet, "/api/ps", nil, &lr); err != nil {
return nil, err
}
return &lr, nil
}
// Copy copies a model - creating a model with another name from an existing
// model.
func (c *Client) Copy(ctx context.Context, req *CopyRequest) error {
if err := c.do(ctx, http.MethodPost, "/api/copy", req, nil); err != nil {
return err
@ -316,7 +313,6 @@ func (c *Client) Copy(ctx context.Context, req *CopyRequest) error {
return nil
}
// Delete deletes a model and its data.
func (c *Client) Delete(ctx context.Context, req *DeleteRequest) error {
if err := c.do(ctx, http.MethodDelete, "/api/delete", req, nil); err != nil {
return err
@ -324,7 +320,6 @@ func (c *Client) Delete(ctx context.Context, req *DeleteRequest) error {
return nil
}
// Show obtains model information, including details, modelfile, license etc.
func (c *Client) Show(ctx context.Context, req *ShowRequest) (*ShowResponse, error) {
var resp ShowResponse
if err := c.do(ctx, http.MethodPost, "/api/show", req, &resp); err != nil {
@ -333,25 +328,12 @@ 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
// returns nil, otherwise an error.
func (c *Client) Heartbeat(ctx context.Context) error {
if err := c.do(ctx, http.MethodHead, "/", nil, nil); err != nil {
return err
}
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.
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 {
@ -360,13 +342,10 @@ func (c *Client) Embeddings(ctx context.Context, req *EmbeddingRequest) (*Embedd
return &resp, nil
}
// CreateBlob creates a blob from a file on the server. digest is the
// expected SHA256 digest of the file, and r represents the file.
func (c *Client) CreateBlob(ctx context.Context, digest string, r io.Reader) error {
return c.do(ctx, http.MethodPost, fmt.Sprintf("/api/blobs/%s", digest), r, nil)
}
// Version returns the Ollama server version as a string.
func (c *Client) Version(ctx context.Context) (string, error) {
var version struct {
Version string `json:"version"`

View File

@ -1,8 +1,6 @@
package api
import (
"testing"
)
import "testing"
func TestClientFromEnvironment(t *testing.T) {
type testCase struct {

View File

@ -2,8 +2,8 @@ package api
import (
"encoding/json"
"errors"
"fmt"
"log/slog"
"math"
"os"
"reflect"
@ -12,7 +12,6 @@ import (
"time"
)
// StatusError is an error with an HTTP status code and message.
type StatusError struct {
StatusCode int
Status string
@ -33,7 +32,6 @@ func (e StatusError) Error() string {
}
}
// ImageData represents the raw binary data of an image file.
type ImageData []byte
// GenerateRequest describes a request sent by [Client.Generate]. While you
@ -47,9 +45,6 @@ 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 +52,7 @@ 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.
@ -82,112 +77,26 @@ type GenerateRequest struct {
Options map[string]interface{} `json:"options"`
}
// ChatRequest describes a request sent by [Client.Chat].
type ChatRequest struct {
// Model is the model name, as in [GenerateRequest].
Model string `json:"model"`
// 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 *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.
Model string `json:"model"`
Messages []Message `json:"messages"`
Stream *bool `json:"stream,omitempty"`
Format string `json:"format"`
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"`
Role string `json:"role"` // one of ["system", "user", "assistant"]
Content string `json:"content"`
Images []ImageData `json:"images,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)
}
// ChatResponse is the response returned by [Client.Chat]. Its fields are
// similar to [GenerateResponse].
type ChatResponse struct {
Model string `json:"model"`
CreatedAt time.Time `json:"created_at"`
Message Message `json:"message"`
DoneReason string `json:"done_reason,omitempty"`
Model string `json:"model"`
CreatedAt time.Time `json:"created_at"`
Message Message `json:"message"`
Done bool `json:"done"`
@ -203,8 +112,7 @@ 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 +122,6 @@ 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"`
@ -231,129 +138,82 @@ 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"`
UseNUMA bool `json:"numa,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGQA int `json:"num_gqa,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"`
// Unused: RopeFrequencyBase is ignored. Instead the value in the model will be used
RopeFrequencyBase float32 `json:"rope_frequency_base,omitempty"`
// Unused: RopeFrequencyScale is ignored. Instead the value in the model will be used
RopeFrequencyScale float32 `json:"rope_frequency_scale,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"`
}
// EmbeddingRequest is the request passed to [Client.Embeddings].
type EmbeddingRequest struct {
// Model is the model name.
Model string `json:"model"`
// Prompt is the textual prompt to embed.
Prompt string `json:"prompt"`
// KeepAlive controls how long the model will stay loaded in memory following
// this request.
Model string `json:"model"`
Prompt string `json:"prompt"`
KeepAlive *Duration `json:"keep_alive,omitempty"`
// Options lists model-specific options.
Options map[string]interface{} `json:"options"`
}
// EmbeddingResponse is the response from [Client.Embeddings].
type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"`
}
// CreateRequest is the request passed to [Client.Create].
type CreateRequest struct {
Model string `json:"model"`
Modelfile string `json:"modelfile"`
Stream *bool `json:"stream,omitempty"`
Quantize string `json:"quantize,omitempty"`
// Deprecated: set the model name with Model instead
Name string `json:"name"`
// Deprecated: set the file content with Modelfile instead
Path string `json:"path"`
// Deprecated: use Quantize instead
Model string `json:"model"`
Path string `json:"path"`
Modelfile string `json:"modelfile"`
Stream *bool `json:"stream,omitempty"`
Quantization string `json:"quantization,omitempty"`
// Name is deprecated, see Model
Name string `json:"name"`
}
// DeleteRequest is the request passed to [Client.Delete].
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].
type CopyRequest struct {
Source string `json:"source"`
Destination string `json:"destination"`
}
// PullRequest is the request passed to [Client.Pull].
type PullRequest struct {
Model string `json:"model"`
Insecure bool `json:"insecure,omitempty"`
@ -361,12 +221,10 @@ 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"`
}
// ProgressResponse is the response passed to progress functions like
// [PullProgressFunc] and [PushProgressFunc].
type ProgressResponse struct {
Status string `json:"status"`
Digest string `json:"digest,omitempty"`
@ -374,7 +232,6 @@ type ProgressResponse struct {
Completed int64 `json:"completed,omitempty"`
}
// PushRequest is the request passed to [Client.Push].
type PushRequest struct {
Model string `json:"model"`
Insecure bool `json:"insecure,omitempty"`
@ -382,22 +239,15 @@ 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 {
type ModelResponse struct {
Name string `json:"name"`
Model string `json:"model"`
ModifiedAt time.Time `json:"modified_at"`
@ -406,53 +256,21 @@ type ListModelResponse struct {
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"`
}
type TokenResponse struct {
Token string `json:"token"`
}
// GenerateResponse is the response passed into [GenerateResponseFunc].
type GenerateResponse struct {
// Model is the model name that generated the response.
Model string `json:"model"`
// CreatedAt is the timestamp of the response.
Model string `json:"model"`
CreatedAt time.Time `json:"created_at"`
Response string `json:"response"`
// Response is the textual response itself.
Response string `json:"response"`
// Done specifies if the response is complete.
Done bool `json:"done"`
// DoneReason is the reason the model stopped generating text.
DoneReason string `json:"done_reason,omitempty"`
// Context is an encoding of the conversation used in this response; this
// can be sent in the next request to keep a conversational memory.
Done bool `json:"done"`
Context []int `json:"context,omitempty"`
Metrics
}
// ModelDetails provides details about a model.
type ModelDetails struct {
ParentModel string `json:"parent_model"`
Format string `json:"format"`
@ -490,6 +308,8 @@ func (m *Metrics) Summary() {
}
}
var ErrInvalidOpts = errors.New("invalid options")
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
@ -503,87 +323,76 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
}
}
invalidOpts := []string{}
for key, val := range m {
opt, ok := jsonOpts[key]
if !ok {
slog.Warn("invalid option provided", "option", key)
continue
}
if opt, ok := jsonOpts[key]; ok {
field := valueOpts.FieldByName(opt.Name)
if field.IsValid() && field.CanSet() {
if val == nil {
continue
}
field := valueOpts.FieldByName(opt.Name)
if field.IsValid() && field.CanSet() {
if val == nil {
continue
}
switch field.Kind() {
case reflect.Int:
switch t := val.(type) {
case int64:
field.SetInt(t)
case float64:
// when JSON unmarshals numbers, it uses float64, not int
field.SetInt(int64(t))
default:
return fmt.Errorf("option %q must be of type integer", key)
}
case reflect.Bool:
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
field.SetBool(val)
case reflect.Float32:
// JSON unmarshals to float64
val, ok := val.(float64)
if !ok {
return fmt.Errorf("option %q must be of type float32", key)
}
field.SetFloat(val)
case reflect.String:
val, ok := val.(string)
if !ok {
return fmt.Errorf("option %q must be of type string", key)
}
field.SetString(val)
case reflect.Slice:
// JSON unmarshals to []interface{}, not []string
val, ok := val.([]interface{})
if !ok {
return fmt.Errorf("option %q must be of type array", key)
}
// convert []interface{} to []string
slice := make([]string, len(val))
for i, item := range val {
str, ok := item.(string)
if !ok {
return fmt.Errorf("option %q must be of an array of strings", key)
switch field.Kind() {
case reflect.Int:
switch t := val.(type) {
case int64:
field.SetInt(t)
case float64:
// when JSON unmarshals numbers, it uses float64, not int
field.SetInt(int64(t))
default:
return fmt.Errorf("option %q must be of type integer", key)
}
slice[i] = str
}
field.Set(reflect.ValueOf(slice))
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
case reflect.Bool:
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())
field.SetBool(val)
case reflect.Float32:
// JSON unmarshals to float64
val, ok := val.(float64)
if !ok {
return fmt.Errorf("option %q must be of type float32", key)
}
field.SetFloat(val)
case reflect.String:
val, ok := val.(string)
if !ok {
return fmt.Errorf("option %q must be of type string", key)
}
field.SetString(val)
case reflect.Slice:
// JSON unmarshals to []interface{}, not []string
val, ok := val.([]interface{})
if !ok {
return fmt.Errorf("option %q must be of type array", key)
}
// convert []interface{} to []string
slice := make([]string, len(val))
for i, item := range val {
str, ok := item.(string)
if !ok {
return fmt.Errorf("option %q must be of an array of strings", key)
}
slice[i] = str
}
field.Set(reflect.ValueOf(slice))
default:
return fmt.Errorf("unknown type loading config params: %v", field.Kind())
}
default:
return fmt.Errorf("unknown type loading config params: %v", field.Kind())
}
} else {
invalidOpts = append(invalidOpts, key)
}
}
if len(invalidOpts) > 0 {
return fmt.Errorf("%w: %v", ErrInvalidOpts, strings.Join(invalidOpts, ", "))
}
return nil
}
// DefaultOptions is the default set of options for [GenerateRequest]; these
// values are used unless the user specifies other values explicitly.
func DefaultOptions() Options {
return Options{
// options set on request to runner
@ -611,10 +420,13 @@ func DefaultOptions() Options {
NumCtx: 2048,
NumBatch: 512,
NumGPU: -1, // -1 here indicates that NumGPU should be set dynamically
NumThread: 0, // let the runtime decide
NumGQA: 1,
NumThread: 0, // let the runtime decide
LowVRAM: false,
F16KV: true,
UseMLock: false,
UseMMap: nil,
UseMMap: true,
UseNUMA: false,
},
}
}
@ -623,13 +435,6 @@ type Duration struct {
time.Duration
}
func (d Duration) MarshalJSON() ([]byte, error) {
if d.Duration < 0 {
return []byte("-1"), nil
}
return []byte("\"" + d.Duration.String() + "\""), nil
}
func (d *Duration) UnmarshalJSON(b []byte) (err error) {
var v any
if err := json.Unmarshal(b, &v); err != nil {
@ -643,7 +448,7 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
if t < 0 {
d.Duration = time.Duration(math.MaxInt64)
} else {
d.Duration = time.Duration(int(t) * int(time.Second))
d.Duration = time.Duration(t * float64(time.Second))
}
case string:
d.Duration, err = time.ParseDuration(t)
@ -653,8 +458,6 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
if d.Duration < 0 {
d.Duration = time.Duration(math.MaxInt64)
}
default:
return fmt.Errorf("Unsupported type: '%s'", reflect.TypeOf(v))
}
return nil
@ -710,17 +513,6 @@ 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"
@ -22,11 +21,6 @@ func TestKeepAliveParsingFromJSON(t *testing.T) {
req: `{ "keep_alive": 42 }`,
exp: &Duration{42 * time.Second},
},
{
name: "Positive Float",
req: `{ "keep_alive": 42.5 }`,
exp: &Duration{42 * time.Second},
},
{
name: "Positive Integer String",
req: `{ "keep_alive": "42m" }`,
@ -37,11 +31,6 @@ func TestKeepAliveParsingFromJSON(t *testing.T) {
req: `{ "keep_alive": -1 }`,
exp: &Duration{math.MaxInt64},
},
{
name: "Negative Float",
req: `{ "keep_alive": -3.14 }`,
exp: &Duration{math.MaxInt64},
},
{
name: "Negative Integer String",
req: `{ "keep_alive": "-1m" }`,
@ -59,175 +48,3 @@ func TestKeepAliveParsingFromJSON(t *testing.T) {
})
}
}
func TestDurationMarshalUnmarshal(t *testing.T) {
tests := []struct {
name string
input time.Duration
expected time.Duration
}{
{
"negative duration",
time.Duration(-1),
time.Duration(math.MaxInt64),
},
{
"positive duration",
42 * time.Second,
42 * time.Second,
},
{
"another positive duration",
42 * time.Minute,
42 * time.Minute,
},
{
"zero duration",
time.Duration(0),
time.Duration(0),
},
{
"max duration",
time.Duration(math.MaxInt64),
time.Duration(math.MaxInt64),
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
b, err := json.Marshal(Duration{test.input})
require.NoError(t, err)
var d Duration
err = json.Unmarshal(b, &d)
require.NoError(t, err)
assert.Equal(t, test.expected, d.Duration, "input %v, marshalled %v, got %v", test.input, string(b), d.Duration)
})
}
}
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)
}
}
}

1
app/.gitignore vendored
View File

@ -1 +1,2 @@
ollama.syso
app

7
app/AppDelegate.h Normal file
View File

@ -0,0 +1,7 @@
#import <Cocoa/Cocoa.h>
@interface AppDelegate : NSObject <NSApplicationDelegate>
- (void)applicationDidFinishLaunching:(NSNotification *)aNotification;
@end

View File

@ -1,10 +1,6 @@
# Ollama App
## Linux
TODO
## MacOS
## macOS
TODO

76
app/app_darwin.go Normal file
View File

@ -0,0 +1,76 @@
package main
// #cgo CFLAGS: -x objective-c
// #cgo LDFLAGS: -framework Cocoa -framework LocalAuthentication -framework ServiceManagement
// #include "app_darwin.h"
import "C"
import (
"context"
"fmt"
"log/slog"
"os"
"path/filepath"
"syscall"
)
func init() {
home, err := os.UserHomeDir()
if err != nil {
panic(err)
}
ServerLogFile = filepath.Join(home, ".ollama", "logs", "server.log")
}
func run() {
initLogging()
slog.Info("ollama macOS app started")
// Ask to move to applications directory
moving := C.askToMoveToApplications()
if moving {
return
}
C.killOtherInstances()
code := C.installSymlink()
if code != 0 {
slog.Error("Failed to install symlink")
}
exe, err := os.Executable()
if err != nil {
panic(err)
}
var options ServerOptions
ctx, cancel := context.WithCancel(context.Background())
var done chan int
done, err = SpawnServer(ctx, filepath.Join(filepath.Dir(exe), "..", "Resources", "ollama"), options)
if err != nil {
slog.Error(fmt.Sprintf("Failed to spawn ollama server %s", err))
done = make(chan int, 1)
done <- 1
}
// Run the native macOS app
// Note: this will block until the app is closed
C.run()
slog.Info("ollama macOS app closed")
cancel()
slog.Info("Waiting for ollama server to shutdown...")
if done != nil {
<-done
}
slog.Info("Ollama app exiting")
}
//export Quit
func Quit() {
syscall.Kill(os.Getpid(), syscall.SIGTERM)
}

13
app/app_darwin.h Normal file
View File

@ -0,0 +1,13 @@
#import <Cocoa/Cocoa.h>
@interface AppDelegate : NSObject <NSApplicationDelegate>
- (void)applicationDidFinishLaunching:(NSNotification *)aNotification;
@end
void run();
void killOtherInstances();
bool askToMoveToApplications();
int createSymlinkWithAuthorization();
int installSymlink();
extern void Restart();
extern void Quit();

282
app/app_darwin.m Normal file
View File

@ -0,0 +1,282 @@
#import <AppKit/AppKit.h>
#import <Cocoa/Cocoa.h>
#import <CoreServices/CoreServices.h>
#import <Security/Security.h>
#import <ServiceManagement/ServiceManagement.h>
#import "app_darwin.h"
@interface AppDelegate ()
@property (strong, nonatomic) NSStatusItem *statusItem;
@end
@implementation AppDelegate
- (void)applicationDidFinishLaunching:(NSNotification *)aNotification {
// show status menu
NSMenu *menu = [[NSMenu alloc] init];
NSMenuItem *aboutMenuItem = [[NSMenuItem alloc] initWithTitle:@"About Ollama" action:@selector(aboutOllama) keyEquivalent:@""];
[aboutMenuItem setTarget:self];
[menu addItem:aboutMenuItem];
// Settings submenu
NSMenu *settingsMenu = [[NSMenu alloc] initWithTitle:@"Settings"];
// Submenu items
NSMenuItem *chooseModelDirectoryItem = [[NSMenuItem alloc] initWithTitle:@"Choose model directory..." action:@selector(chooseModelDirectory) keyEquivalent:@""];
[chooseModelDirectoryItem setTarget:self];
[chooseModelDirectoryItem setEnabled:YES];
[settingsMenu addItem:chooseModelDirectoryItem];
NSMenuItem *exposeExternallyItem = [[NSMenuItem alloc] initWithTitle:@"Allow external connections" action:@selector(toggleExposeExternally:) keyEquivalent:@""];
[exposeExternallyItem setTarget:self];
[exposeExternallyItem setState:NSOffState]; // Set initial state to off
[exposeExternallyItem setEnabled:YES];
[settingsMenu addItem:exposeExternallyItem];
NSMenuItem *allowCrossOriginItem = [[NSMenuItem alloc] initWithTitle:@"Allow browser requests" action:@selector(toggleCrossOrigin:) keyEquivalent:@""];
[allowCrossOriginItem setTarget:self];
[allowCrossOriginItem setState:NSOffState]; // Set initial state to off
[allowCrossOriginItem setEnabled:YES];
[settingsMenu addItem:allowCrossOriginItem];
NSMenuItem *settingsMenuItem = [[NSMenuItem alloc] initWithTitle:@"Settings" action:nil keyEquivalent:@""];
[settingsMenuItem setSubmenu:settingsMenu];
[menu addItem:settingsMenuItem];
[menu addItemWithTitle:@"Quit Ollama" action:@selector(quit) keyEquivalent:@"q"];
self.statusItem = [[NSStatusBar systemStatusBar] statusItemWithLength:NSVariableStatusItemLength];
[self.statusItem addObserver:self forKeyPath:@"button.effectiveAppearance" options:NSKeyValueObservingOptionNew|NSKeyValueObservingOptionInitial context:nil];
self.statusItem.menu = menu;
[self showIcon];
}
- (void)aboutOllama {
[[NSApplication sharedApplication] orderFrontStandardAboutPanel:nil];
}
- (void)toggleCrossOrigin:(id)sender {
NSMenuItem *item = (NSMenuItem *)sender;
if ([item state] == NSOffState) {
// Do something when cross-origin requests are allowed
[item setState:NSOnState];
} else {
// Do something when cross-origin requests are disallowed
[item setState:NSOffState];
}
}
- (void)toggleExposeExternally:(id)sender {
NSMenuItem *item = (NSMenuItem *)sender;
if ([item state] == NSOffState) {
// Do something when Ollama is exposed externally
[item setState:NSOnState];
} else {
// Do something when Ollama is not exposed externally
[item setState:NSOffState];
}
}
- (void)chooseModelDirectory {
NSOpenPanel *openPanel = [NSOpenPanel openPanel];
[openPanel setCanChooseFiles:NO];
[openPanel setCanChooseDirectories:YES];
[openPanel setAllowsMultipleSelection:NO];
NSInteger result = [openPanel runModal];
if (result == NSModalResponseOK) {
NSURL *selectedDirectoryURL = [openPanel URLs].firstObject;
// Do something with the selected directory URL
}
}
-(void) showIcon {
NSAppearance* appearance = self.statusItem.button.effectiveAppearance;
NSString* appearanceName = (NSString*)(appearance.name);
NSString* iconName = [[appearanceName lowercaseString] containsString:@"dark"] ? @"iconDark" : @"icon";
NSImage* statusImage = [NSImage imageNamed:iconName];
[statusImage setTemplate:YES];
self.statusItem.button.image = statusImage;
}
-(void)observeValueForKeyPath:(NSString *)keyPath ofObject:(id)object change:(NSDictionary<NSKeyValueChangeKey,id> *)change context:(void *)context {
[self showIcon];
}
- (void)quit {
[NSApp stop:nil];
}
@end
void run() {
@autoreleasepool {
[NSApplication sharedApplication];
AppDelegate *appDelegate = [[AppDelegate alloc] init];
[NSApp setDelegate:appDelegate];
[NSApp run];
}
}
// killOtherInstances kills all other instances of the app currently
// running. This way we can ensure that only the most recently started
// instance of Ollama is running
void killOtherInstances() {
pid_t pid = getpid();
NSArray *all = [[NSWorkspace sharedWorkspace] runningApplications];
NSMutableArray *apps = [NSMutableArray array];
for (NSRunningApplication *app in all) {
if ([app.bundleIdentifier isEqualToString:[[NSBundle mainBundle] bundleIdentifier]] ||
[app.bundleIdentifier isEqualToString:@"ai.ollama.ollama"] ||
[app.bundleIdentifier isEqualToString:@"com.electron.ollama"]) {
if (app.processIdentifier != pid) {
[apps addObject:app];
}
}
}
for (NSRunningApplication *app in apps) {
kill(app.processIdentifier, SIGTERM);
}
NSDate *startTime = [NSDate date];
for (NSRunningApplication *app in apps) {
while (!app.terminated) {
if (-[startTime timeIntervalSinceNow] >= 5) {
kill(app.processIdentifier, SIGKILL);
break;
}
[[NSRunLoop currentRunLoop] runUntilDate:[NSDate dateWithTimeIntervalSinceNow:0.1]];
}
}
}
bool askToMoveToApplications() {
NSString *bundlePath = [[NSBundle mainBundle] bundlePath];
if ([bundlePath hasPrefix:@"/Applications"]) {
return false;
}
NSAlert *alert = [[NSAlert alloc] init];
[alert setMessageText:@"Move to Applications?"];
[alert setInformativeText:@"Ollama works best when run from the Applications directory."];
[alert addButtonWithTitle:@"Move to Applications"];
[alert addButtonWithTitle:@"Don't move"];
[NSApp activateIgnoringOtherApps:YES];
if ([alert runModal] != NSAlertFirstButtonReturn) {
return false;
}
// move to applications
NSString *applicationsPath = @"/Applications";
NSString *newPath = [applicationsPath stringByAppendingPathComponent:@"Ollama.app"];
NSFileManager *fileManager = [NSFileManager defaultManager];
// Check if the newPath already exists
if ([fileManager fileExistsAtPath:newPath]) {
NSError *removeError = nil;
[fileManager removeItemAtPath:newPath error:&removeError];
if (removeError) {
NSLog(@"Error removing file at %@: %@", newPath, removeError);
return false; // or handle the error
}
}
NSError *moveError = nil;
[fileManager moveItemAtPath:bundlePath toPath:newPath error:&moveError];
if (moveError) {
NSLog(@"Error moving file from %@ to %@: %@", bundlePath, newPath, moveError);
return false;
}
NSLog(@"Opening %@", newPath);
NSError *error = nil;
NSWorkspace *workspace = [NSWorkspace sharedWorkspace];
#pragma clang diagnostic ignored "-Wdeprecated-declarations"
[workspace launchApplicationAtURL:[NSURL fileURLWithPath:newPath]
options:NSWorkspaceLaunchNewInstance | NSWorkspaceLaunchDefault
configuration:@{}
error:&error];
return true;
}
int installSymlink() {
NSString *linkPath = @"/usr/local/bin/ollama";
NSError *error = nil;
NSFileManager *fileManager = [NSFileManager defaultManager];
NSString *symlinkPath = [fileManager destinationOfSymbolicLinkAtPath:linkPath error:&error];
NSString *bundlePath = [[NSBundle mainBundle] bundlePath];
NSString *execPath = [[NSBundle mainBundle] executablePath];
NSString *resPath = [[NSBundle mainBundle] pathForResource:@"ollama" ofType:nil];
// if the symlink already exists and points to the right place, don't prompt
if ([symlinkPath isEqualToString:resPath]) {
NSLog(@"symbolic link already exists and points to the right place");
return 0;
}
NSString *authorizationPrompt = @"Ollama is trying to install its command line interface (CLI) tool.";
AuthorizationRef auth = NULL;
OSStatus createStatus = AuthorizationCreate(NULL, kAuthorizationEmptyEnvironment, kAuthorizationFlagDefaults, &auth);
if (createStatus != errAuthorizationSuccess) {
NSLog(@"Error creating authorization");
return -1;
}
NSString * bundleIdentifier = [[NSBundle mainBundle] bundleIdentifier];
NSString *rightNameString = [NSString stringWithFormat:@"%@.%@", bundleIdentifier, @"auth3"];
const char *rightName = rightNameString.UTF8String;
OSStatus getRightResult = AuthorizationRightGet(rightName, NULL);
if (getRightResult == errAuthorizationDenied) {
if (AuthorizationRightSet(auth, rightName, (__bridge CFTypeRef _Nonnull)(@(kAuthorizationRuleAuthenticateAsAdmin)), (__bridge CFStringRef _Nullable)(authorizationPrompt), NULL, NULL) != errAuthorizationSuccess) {
NSLog(@"Failed to set right");
return -1;
}
}
AuthorizationItem right = { .name = rightName, .valueLength = 0, .value = NULL, .flags = 0 };
AuthorizationRights rights = { .count = 1, .items = &right };
AuthorizationFlags flags = (AuthorizationFlags)(kAuthorizationFlagExtendRights | kAuthorizationFlagInteractionAllowed);
AuthorizationItem iconAuthorizationItem = {.name = kAuthorizationEnvironmentIcon, .valueLength = 0, .value = NULL, .flags = 0};
AuthorizationEnvironment authorizationEnvironment = {.count = 0, .items = NULL};
BOOL failedToUseSystemDomain = NO;
OSStatus copyStatus = AuthorizationCopyRights(auth, &rights, &authorizationEnvironment, flags, NULL);
if (copyStatus != errAuthorizationSuccess) {
failedToUseSystemDomain = YES;
if (copyStatus == errAuthorizationCanceled) {
NSLog(@"User cancelled authorization");
return -1;
} else {
NSLog(@"Failed copying system domain rights: %d", copyStatus);
return -1;
}
}
const char *toolPath = "/bin/ln";
const char *args[] = {"-s", "-F", [resPath UTF8String], "/usr/local/bin/ollama", NULL};
FILE *pipe = NULL;
#pragma clang diagnostic ignored "-Wdeprecated-declarations"
OSStatus status = AuthorizationExecuteWithPrivileges(auth, toolPath, kAuthorizationFlagDefaults, (char *const *)args, &pipe);
if (status != errAuthorizationSuccess) {
NSLog(@"Failed to create symlink");
return -1;
}
AuthorizationFree(auth, kAuthorizationFlagDestroyRights);
return 0;
}

166
app/app_windows.go Normal file
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@ -0,0 +1,166 @@
package main
import (
"context"
"errors"
"fmt"
"log"
"log/slog"
"os"
"os/exec"
"os/signal"
"path/filepath"
"strings"
"syscall"
"github.com/ollama/ollama/app/lifecycle"
"github.com/ollama/ollama/app/store"
"github.com/ollama/ollama/app/tray"
"github.com/ollama/ollama/app/updater"
)
func init() {
AppName += ".exe"
CLIName += ".exe"
// Logs, configs, downloads go to LOCALAPPDATA
localAppData := os.Getenv("LOCALAPPDATA")
AppDataDir = filepath.Join(localAppData, "Ollama")
AppLogFile = filepath.Join(AppDataDir, "app.log")
ServerLogFile = filepath.Join(AppDataDir, "server.log")
// 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"), ";")
// Start with whatever we find in the PATH/LD_LIBRARY_PATH
found := false
for _, path := range paths {
d, err := filepath.Abs(path)
if err != nil {
continue
}
if strings.EqualFold(AppDir, d) {
found = true
}
}
if !found {
paths = append(paths, AppDir)
pathVal := strings.Join(paths, ";")
slog.Debug("setting PATH=" + pathVal)
err := os.Setenv("PATH", pathVal)
if err != nil {
slog.Error(fmt.Sprintf("failed to update PATH: %s", err))
}
}
// Make sure our logging dir exists
_, 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))
}
}
}
func ShowLogs() {
cmd_path := "c:\\Windows\\system32\\cmd.exe"
slog.Debug(fmt.Sprintf("viewing logs with start %s", AppDataDir))
cmd := exec.Command(cmd_path, "/c", "start", AppDataDir)
cmd.SysProcAttr = &syscall.SysProcAttr{HideWindow: false, CreationFlags: 0x08000000}
err := cmd.Start()
if err != nil {
slog.Error(fmt.Sprintf("Failed to open log dir: %s", err))
}
}
func Start() {
cmd_path := "c:\\Windows\\system32\\cmd.exe"
slog.Debug(fmt.Sprintf("viewing logs with start %s", AppDataDir))
cmd := exec.Command(cmd_path, "/c", "start", AppDataDir)
cmd.SysProcAttr = &syscall.SysProcAttr{HideWindow: false, CreationFlags: 0x08000000}
err := cmd.Start()
if err != nil {
slog.Error(fmt.Sprintf("Failed to open log dir: %s", err))
}
}
func run() {
initLogging()
slog.Info("ollama windows app started")
ctx, cancel := context.WithCancel(context.Background())
var done chan int
t, err := tray.NewTray()
if err != nil {
log.Fatalf("Failed to start: %s", err)
}
callbacks := t.GetCallbacks()
signals := make(chan os.Signal, 1)
signal.Notify(signals, syscall.SIGINT, syscall.SIGTERM)
go func() {
slog.Debug("starting callback loop")
for {
select {
case <-callbacks.Quit:
slog.Debug("quit called")
t.Quit()
case <-signals:
slog.Debug("shutting down due to signal")
t.Quit()
case <-callbacks.Update:
err := updater.DoUpgrade(cancel, done)
if err != nil {
slog.Warn(fmt.Sprintf("upgrade attempt failed: %s", err))
}
case <-callbacks.ShowLogs:
ShowLogs()
case <-callbacks.DoFirstUse:
err := lifecycle.GetStarted()
if err != nil {
slog.Warn(fmt.Sprintf("Failed to launch getting started shell: %s", err))
}
}
}
}()
if !store.GetFirstTimeRun() {
slog.Debug("First time run")
err = t.DisplayFirstUseNotification()
if err != nil {
slog.Debug(fmt.Sprintf("XXX failed to display first use notification %v", err))
}
store.SetFirstTimeRun(true)
} else {
slog.Debug("Not first time, skipping first run notification")
}
if isServerRunning(ctx) {
slog.Info("Detected another instance of ollama running, exiting")
os.Exit(1)
}
done, err = SpawnServer(ctx, CLIName)
if err != nil {
// TODO - should we retry in a backoff loop?
// TODO - should we pop up a warning and maybe add a menu item to view application logs?
slog.Error(fmt.Sprintf("Failed to spawn ollama server %s", err))
done = make(chan int, 1)
done <- 1
}
updater.StartBackgroundUpdaterChecker(ctx, t.UpdateAvailable)
t.Run()
cancel()
slog.Info("Waiting for ollama server to shutdown...")
if done != nil {
<-done
}
slog.Info("Ollama app exiting")
}

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@ -0,0 +1,40 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDisplayName</key>
<string>Ollama</string>
<key>CFBundleExecutable</key>
<string>Ollama</string>
<key>CFBundleIconFile</key>
<string>icon.icns</string>
<key>CFBundleIdentifier</key>
<string>com.ollama.ollama</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>Ollama</string>
<key>CFBundlePackageType</key>
<string>APPL</string>
<key>CFBundleShortVersionString</key>
<string>0.0.0</string>
<key>CFBundleVersion</key>
<string>0.0.0</string>
<key>DTCompiler</key>
<string>com.apple.compilers.llvm.clang.1_0</string>
<key>DTSDKBuild</key>
<string>22E245</string>
<key>DTSDKName</key>
<string>macosx13.3</string>
<key>DTXcode</key>
<string>1431</string>
<key>DTXcodeBuild</key>
<string>14E300c</string>
<key>LSApplicationCategoryType</key>
<string>public.app-category.developer-tools</string>
<key>LSMinimumSystemVersion</key>
<string>11.0</string>
<key>LSUIElement</key>
<true/>
</dict>
</plist>

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@ -0,0 +1,7 @@
package lifecycle
import "fmt"
func GetStarted() error {
return fmt.Errorf("GetStarted not implemented")
}

View File

@ -1,9 +0,0 @@
//go:build !windows
package lifecycle
import "errors"
func GetStarted() error {
return errors.New("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

@ -1,94 +0,0 @@
package lifecycle
import (
"context"
"fmt"
"log"
"log/slog"
"os"
"os/signal"
"syscall"
"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
t, err := tray.NewTray()
if err != nil {
log.Fatalf("Failed to start: %s", err)
}
callbacks := t.GetCallbacks()
signals := make(chan os.Signal, 1)
signal.Notify(signals, syscall.SIGINT, syscall.SIGTERM)
go func() {
slog.Debug("starting callback loop")
for {
select {
case <-callbacks.Quit:
slog.Debug("quit called")
t.Quit()
case <-signals:
slog.Debug("shutting down due to signal")
t.Quit()
case <-callbacks.Update:
err := DoUpgrade(cancel, done)
if err != nil {
slog.Warn(fmt.Sprintf("upgrade attempt failed: %s", err))
}
case <-callbacks.ShowLogs:
ShowLogs()
case <-callbacks.DoFirstUse:
err := GetStarted()
if err != nil {
slog.Warn(fmt.Sprintf("Failed to launch getting started shell: %s", err))
}
}
}
}()
// Are we first use?
if !store.GetFirstTimeRun() {
slog.Debug("First time run")
err = t.DisplayFirstUseNotification()
if err != nil {
slog.Debug(fmt.Sprintf("XXX failed to display first use notification %v", err))
}
store.SetFirstTimeRun(true)
} else {
slog.Debug("Not first time, skipping first run notification")
}
if IsServerRunning(ctx) {
slog.Info("Detected another instance of ollama running, exiting")
os.Exit(1)
} else {
done, err = SpawnServer(ctx, CLIName)
if err != nil {
// TODO - should we retry in a backoff loop?
// TODO - should we pop up a warning and maybe add a menu item to view application logs?
slog.Error(fmt.Sprintf("Failed to spawn ollama server %s", err))
done = make(chan int, 1)
done <- 1
}
}
StartBackgroundUpdaterChecker(ctx, t.UpdateAvailable)
t.Run()
cancel()
slog.Info("Waiting for ollama server to shutdown...")
if done != nil {
<-done
}
slog.Info("Ollama app exiting")
}

View File

@ -1,80 +0,0 @@
package lifecycle
import (
"fmt"
"log/slog"
"os"
"path/filepath"
"strconv"
"strings"
"github.com/ollama/ollama/envconfig"
)
func InitLogging() {
level := slog.LevelInfo
if envconfig.Debug() {
level = slog.LevelDebug
}
var logFile *os.File
var err error
// Detect if we're a GUI app on windows, and if not, send logs to console
if os.Stderr.Fd() != 0 {
// Console app detected
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)
if err != nil {
slog.Error(fmt.Sprintf("failed to create server log %v", err))
return
}
}
handler := slog.NewTextHandler(logFile, &slog.HandlerOptions{
Level: level,
AddSource: true,
ReplaceAttr: func(_ []string, attr slog.Attr) slog.Attr {
if attr.Key == slog.SourceKey {
source := attr.Value.Any().(*slog.Source)
source.File = filepath.Base(source.File)
}
return attr
},
})
slog.SetDefault(slog.New(handler))
slog.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

@ -1,9 +0,0 @@
//go:build !windows
package lifecycle
import "log/slog"
func ShowLogs() {
slog.Warn("not 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

@ -1,19 +0,0 @@
package lifecycle
import (
"fmt"
"log/slog"
"os/exec"
"syscall"
)
func ShowLogs() {
cmd_path := "c:\\Windows\\system32\\cmd.exe"
slog.Debug(fmt.Sprintf("viewing logs with start %s", AppDataDir))
cmd := exec.Command(cmd_path, "/c", "start", AppDataDir)
cmd.SysProcAttr = &syscall.SysProcAttr{HideWindow: false, CreationFlags: 0x08000000}
err := cmd.Start()
if err != nil {
slog.Error(fmt.Sprintf("Failed to open log dir: %s", err))
}
}

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"), ";")
@ -69,16 +63,12 @@ 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"
// } else if runtime.GOOS == "linux" {
// TODO
}
}

44
app/log.go Normal file
View File

@ -0,0 +1,44 @@
package main
import (
"fmt"
"log/slog"
"os"
"path/filepath"
)
func initLogging() {
level := slog.LevelInfo
if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" {
level = slog.LevelDebug
}
var logFile *os.File
var err error
// Detect if we're a GUI app on windows, and if not, send logs to console
if os.Stderr.Fd() != 0 {
// Console app detected
logFile = os.Stderr
// TODO - write one-line to the app.log file saying we're running in console mode to help avoid confusion
} else {
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
}
}
handler := slog.NewTextHandler(logFile, &slog.HandlerOptions{
Level: level,
AddSource: true,
ReplaceAttr: func(_ []string, attr slog.Attr) slog.Attr {
if attr.Key == slog.SourceKey {
source := attr.Value.Any().(*slog.Source)
source.File = filepath.Base(source.File)
}
return attr
},
})
slog.SetDefault(slog.New(handler))
}

View File

@ -2,11 +2,15 @@ package main
// Compile with the following to get rid of the cmd pop up on windows
// go build -ldflags="-H windowsgui" .
import (
"github.com/ollama/ollama/app/lifecycle"
var (
AppName string
CLIName string
AppDir string
AppDataDir string
AppLogFile string
ServerLogFile string
)
func main() {
lifecycle.Run()
run()
}

View File

@ -1,4 +1,4 @@
package lifecycle
package main
import (
"context"
@ -14,43 +14,28 @@ import (
"github.com/ollama/ollama/api"
)
func getCLIFullPath(command string) string {
var cmdPath string
appExe, err := os.Executable()
if err == nil {
// Check both the same location as the tray app, as well as ./bin
cmdPath = filepath.Join(filepath.Dir(appExe), command)
_, err := os.Stat(cmdPath)
if err == nil {
return cmdPath
}
cmdPath = filepath.Join(filepath.Dir(appExe), "bin", command)
_, err = os.Stat(cmdPath)
if err == nil {
return cmdPath
}
}
cmdPath, err = exec.LookPath(command)
if err == nil {
_, err := os.Stat(cmdPath)
if err == nil {
return cmdPath
}
}
pwd, err := os.Getwd()
if err == nil {
cmdPath = filepath.Join(pwd, command)
_, err = os.Stat(cmdPath)
if err == nil {
return cmdPath
}
}
return command
type ServerOptions struct {
Cors bool
Expose bool
ModelsPath string
}
func start(ctx context.Context, command string) (*exec.Cmd, error) {
cmd := getCmd(ctx, getCLIFullPath(command))
func start(ctx context.Context, command string, options ServerOptions) (*exec.Cmd, error) {
cmd := getCmd(ctx, command)
// set environment variables
if options.ModelsPath != "" {
cmd.Env = append(cmd.Env, fmt.Sprintf("OLLAMA_MODELS=%s", options.ModelsPath))
}
if options.Cors {
cmd.Env = append(cmd.Env, "OLLAMA_ORIGINS=*")
}
if options.Expose {
cmd.Env = append(cmd.Env, "OLLAMA_HOST=0.0.0.0")
}
stdout, err := cmd.StdoutPipe()
if err != nil {
return nil, fmt.Errorf("failed to spawn server stdout pipe: %w", err)
@ -60,24 +45,11 @@ 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)
}
logDir := filepath.Dir(ServerLogFile)
_, err = os.Stat(logDir)
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 {
return nil, fmt.Errorf("create ollama server log dir %s: %v", logDir, err)
}
}
go func() {
defer logFile.Close()
io.Copy(logFile, stdout) //nolint:errcheck
@ -131,20 +103,25 @@ func start(ctx context.Context, command string) (*exec.Cmd, error) {
return cmd, nil
}
func SpawnServer(ctx context.Context, command string) (chan int, error) {
func SpawnServer(ctx context.Context, command string, options ServerOptions) (chan int, error) {
logDir := filepath.Dir(ServerLogFile)
_, err := os.Stat(logDir)
if errors.Is(err, os.ErrNotExist) {
if err := os.MkdirAll(logDir, 0o755); err != nil {
return nil, fmt.Errorf("create ollama server log dir %s: %v", logDir, err)
}
}
done := make(chan int)
go func() {
// Keep the server running unless we're shuttind down the app
crashCount := 0
for {
slog.Info("starting server...")
cmd, err := start(ctx, command)
slog.Info(fmt.Sprintf("starting server..."))
cmd, err := start(ctx, command, options)
if err != nil {
crashCount++
slog.Error(fmt.Sprintf("failed to start server %s", err))
time.Sleep(500 * time.Millisecond * time.Duration(crashCount))
continue
}
cmd.Wait() //nolint:errcheck
@ -170,7 +147,7 @@ func SpawnServer(ctx context.Context, command string) (chan int, error) {
return done, nil
}
func IsServerRunning(ctx context.Context) bool {
func isServerRunning(ctx context.Context) bool {
client, err := api.ClientFromEnvironment()
if err != nil {
slog.Info("unable to connect to server")

View File

@ -1,6 +1,4 @@
//go:build !windows
package lifecycle
package main
import (
"context"

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@ -1,4 +1,4 @@
package lifecycle
package main
import (
"context"
@ -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)

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

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@ -1,13 +1,11 @@
//go:build !windows
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")
}

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@ -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

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@ -1,72 +1,71 @@
//go:build windows
package wintray
import (
"fmt"
"log/slog"
"unsafe"
"golang.org/x/sys/windows"
)
const (
_ = iota
updateAvailableMenuID
updateMenuID
separatorMenuID
diagLogsMenuID
diagSeparatorMenuID
quitMenuID
)
func (t *winTray) initMenus() error {
if err := t.addOrUpdateMenuItem(diagLogsMenuID, 0, diagLogsMenuTitle, false); err != nil {
return fmt.Errorf("unable to create menu entries %w\n", err)
}
if err := t.addSeparatorMenuItem(diagSeparatorMenuID, 0); err != nil {
return fmt.Errorf("unable to create menu entries %w", err)
}
if err := t.addOrUpdateMenuItem(quitMenuID, 0, quitMenuTitle, false); err != nil {
return fmt.Errorf("unable to create menu entries %w\n", err)
}
return nil
}
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 {
return fmt.Errorf("unable to create menu entries %w", err)
}
if err := t.addOrUpdateMenuItem(updateMenuID, 0, updateMenutTitle, false); err != nil {
return fmt.Errorf("unable to create menu entries %w", err)
}
if err := t.addSeparatorMenuItem(separatorMenuID, 0); err != nil {
return fmt.Errorf("unable to create menu entries %w", err)
}
iconFilePath, err := iconBytesToFilePath(wt.updateIcon)
if err != nil {
return fmt.Errorf("unable to write icon data to temp file: %w", err)
}
if err := wt.setIcon(iconFilePath); err != nil {
return fmt.Errorf("unable to set icon: %w", err)
}
t.updateNotified = true
t.pendingUpdate = true
// Now pop up the notification
t.muNID.Lock()
defer t.muNID.Unlock()
copy(t.nid.InfoTitle[:], windows.StringToUTF16(updateTitle))
copy(t.nid.Info[:], windows.StringToUTF16(fmt.Sprintf(updateMessage, ver)))
t.nid.Flags |= NIF_INFO
t.nid.Timeout = 10
t.nid.Size = uint32(unsafe.Sizeof(*wt.nid))
err = t.nid.modify()
if err != nil {
return err
}
}
return nil
}
//go:build windows
package wintray
import (
"fmt"
"log/slog"
"unsafe"
"golang.org/x/sys/windows"
)
const (
updatAvailableMenuID = 1
updateMenuID = updatAvailableMenuID + 1
separatorMenuID = updateMenuID + 1
diagLogsMenuID = separatorMenuID + 1
diagSeparatorMenuID = diagLogsMenuID + 1
quitMenuID = diagSeparatorMenuID + 1
)
func (t *winTray) initMenus() error {
if err := t.addOrUpdateMenuItem(diagLogsMenuID, 0, diagLogsMenuTitle, false); err != nil {
return fmt.Errorf("unable to create menu entries %w\n", err)
}
if err := t.addSeparatorMenuItem(diagSeparatorMenuID, 0); err != nil {
return fmt.Errorf("unable to create menu entries %w", err)
}
if err := t.addOrUpdateMenuItem(quitMenuID, 0, quitMenuTitle, false); err != nil {
return fmt.Errorf("unable to create menu entries %w\n", err)
}
return nil
}
func (t *winTray) UpdateAvailable(ver string) error {
if !t.updateNotified {
slog.Debug("updating menu and sending notification for new update")
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 {
return fmt.Errorf("unable to create menu entries %w", err)
}
if err := t.addSeparatorMenuItem(separatorMenuID, 0); err != nil {
return fmt.Errorf("unable to create menu entries %w", err)
}
iconFilePath, err := iconBytesToFilePath(wt.updateIcon)
if err != nil {
return fmt.Errorf("unable to write icon data to temp file: %w", err)
}
if err := wt.setIcon(iconFilePath); err != nil {
return fmt.Errorf("unable to set icon: %w", err)
}
t.updateNotified = true
t.pendingUpdate = true
// Now pop up the notification
t.muNID.Lock()
defer t.muNID.Unlock()
copy(t.nid.InfoTitle[:], windows.StringToUTF16(updateTitle))
copy(t.nid.Info[:], windows.StringToUTF16(fmt.Sprintf(updateMessage, ver)))
t.nid.Flags |= NIF_INFO
t.nid.Timeout = 10
t.nid.Size = uint32(unsafe.Sizeof(*wt.nid))
err = t.nid.modify()
if err != nil {
return err
}
}
return 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

@ -1,4 +1,4 @@
package lifecycle
package updater
import (
"context"
@ -15,7 +15,6 @@ import (
"path"
"path/filepath"
"runtime"
"strconv"
"strings"
"time"
@ -23,6 +22,10 @@ import (
"github.com/ollama/ollama/version"
)
var (
UpdateStageDir string
)
var (
UpdateCheckURLBase = "https://ollama.com/api/update"
UpdateDownloaded = false
@ -47,7 +50,7 @@ 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 +82,7 @@ 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 +91,7 @@ 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 +118,7 @@ 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()
@ -124,7 +127,7 @@ func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
slog.Debug("no etag detected, falling back to filename based dedup")
etag = "_"
}
filename := Installer
filename := "OllamaSetup.exe"
_, params, err := mime.ParseMediaType(resp.Header.Get("content-disposition"))
if err == nil {
filename = params["filename"]

View File

@ -1,12 +1,10 @@
//go:build !windows
package lifecycle
package updater
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

@ -1,8 +1,7 @@
package lifecycle
package updater
import (
"context"
"errors"
"fmt"
"log/slog"
"os"
@ -10,13 +9,19 @@ import (
"path/filepath"
)
func init() {
UpdateStageDir = filepath.Join(os.Getenv("LOCALAPPDATA"), "Ollama", "updates")
}
func DoUpgrade(cancel context.CancelFunc, done chan int) error {
logFile := filepath.Join(os.Getenv("LOCALAPPDATA"), "Ollama", "upgrade.log")
files, err := filepath.Glob(filepath.Join(UpdateStageDir, "*", "*.exe")) // TODO generalize for multiplatform
if err != nil {
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))
@ -24,17 +29,24 @@ func DoUpgrade(cancel context.CancelFunc, done chan int) error {
installerExe := files[0]
slog.Info("starting upgrade with " + installerExe)
slog.Info("upgrade log file " + UpgradeLogFile)
slog.Info("upgrade log file " + logFile)
// 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",
"/CLOSEAPPLICATIONS", // Quit the tray app if it's still running
"/LOG=" + filepath.Base(logFile), // Only relative seems reliable, so set pwd
"/FORCECLOSEAPPLICATIONS", // Force close the tray app - might be needed
}
// When we're not in debug mode, make the upgrade as quiet as possible (no GUI, no prompts)
// TODO - temporarily disable since we're pinning in debug mode for the preview
// if debug := os.Getenv("OLLAMA_DEBUG"); debug == "" {
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")
@ -47,7 +59,7 @@ func DoUpgrade(cancel context.CancelFunc, done chan int) error {
}
slog.Debug(fmt.Sprintf("starting installer: %s %v", installerExe, installArgs))
os.Chdir(filepath.Dir(UpgradeLogFile)) //nolint:errcheck
os.Chdir(filepath.Dir(logFile)) //nolint:errcheck
cmd := exec.Command(installerExe, installArgs...)
if err := cmd.Start(); err != nil {
@ -61,7 +73,7 @@ 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-amd64\*.dll"; DestDir: "{app}"; Flags: ignoreversion 64bit
Source: "..\dist\windows-amd64\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 llama2"
write-host ""

View File

@ -5,50 +5,17 @@ import (
"context"
"crypto/rand"
"encoding/base64"
"errors"
"fmt"
"io"
"log/slog"
"os"
"path/filepath"
"strings"
"golang.org/x/crypto/ssh"
)
const defaultPrivateKey = "id_ed25519"
func keyPath() (string, error) {
home, err := os.UserHomeDir()
if err != nil {
return "", err
}
return filepath.Join(home, ".ollama", defaultPrivateKey), nil
}
func GetPublicKey() (string, error) {
keyPath, err := keyPath()
if err != nil {
return "", err
}
privateKeyFile, err := os.ReadFile(keyPath)
if err != nil {
slog.Info(fmt.Sprintf("Failed to load private key: %v", err))
return "", err
}
privateKey, err := ssh.ParsePrivateKey(privateKeyFile)
if err != nil {
return "", err
}
publicKey := ssh.MarshalAuthorizedKey(privateKey.PublicKey())
return strings.TrimSpace(string(publicKey)), nil
}
func NewNonce(r io.Reader, length int) (string, error) {
nonce := make([]byte, length)
if _, err := io.ReadFull(r, nonce); err != nil {
@ -59,11 +26,13 @@ func NewNonce(r io.Reader, length int) (string, error) {
}
func Sign(ctx context.Context, bts []byte) (string, error) {
keyPath, err := keyPath()
home, err := os.UserHomeDir()
if err != nil {
return "", err
}
keyPath := filepath.Join(home, ".ollama", defaultPrivateKey)
privateKeyFile, err := os.ReadFile(keyPath)
if err != nil {
slog.Info(fmt.Sprintf("Failed to load private key: %v", err))
@ -79,7 +48,7 @@ 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

File diff suppressed because it is too large Load Diff

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"
@ -9,17 +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"
)
type MultilineState int
@ -28,16 +25,75 @@ 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{},
}
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")
fmt.Fprintln(os.Stderr, " /show Show model information")
fmt.Fprintln(os.Stderr, " /load <model> Load a session or model")
fmt.Fprintln(os.Stderr, " /save <model> Save your current session")
fmt.Fprintln(os.Stderr, " /clear Clear session context")
fmt.Fprintln(os.Stderr, " /bye Exit")
fmt.Fprintln(os.Stderr, " /?, /help Help for a command")
fmt.Fprintln(os.Stderr, " /? shortcuts Help for keyboard shortcuts")
@ -55,6 +111,7 @@ 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")
@ -74,7 +131,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
fmt.Fprintln(os.Stderr, " Alt + f Move forward (right) one word")
fmt.Fprintln(os.Stderr, " Ctrl + k Delete the sentence after the cursor")
fmt.Fprintln(os.Stderr, " Ctrl + u Delete the sentence before the cursor")
fmt.Fprintln(os.Stderr, " Ctrl + w Delete the word before the cursor")
fmt.Fprintln(os.Stderr, "")
fmt.Fprintln(os.Stderr, " Ctrl + l Clear the screen")
fmt.Fprintln(os.Stderr, " Ctrl + c Stop the model from responding")
@ -100,13 +156,12 @@ 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")
fmt.Fprintln(os.Stderr, " /set parameter repeat_last_n <int> Set how far back to look for repetitions")
fmt.Fprintln(os.Stderr, " /set parameter num_gpu <int> The number of layers to send to the GPU")
fmt.Fprintln(os.Stderr, " /set parameter stop <string> <string> ... Set the stop parameters")
fmt.Fprintln(os.Stderr, " /set parameter stop \"<string>\", ... Set the stop parameters")
fmt.Fprintln(os.Stderr, "")
}
@ -120,10 +175,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
return err
}
if envconfig.NoHistory() {
scanner.HistoryDisable()
}
fmt.Print(readline.StartBracketedPaste)
defer fmt.Printf(readline.EndBracketedPaste)
@ -165,6 +216,10 @@ 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 +251,7 @@ 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
@ -220,22 +275,11 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
fn := func(resp api.ProgressResponse) error { return nil }
err = client.Create(cmd.Context(), req, fn)
if err != nil {
if strings.Contains(err.Error(), errtypes.InvalidModelNameErrMsg) {
fmt.Printf("error: The model name '%s' is invalid\n", args[1])
continue
}
fmt.Println("error: couldn't save model")
return err
}
fmt.Printf("Created new model '%s'\n", args[1])
continue
case strings.HasPrefix(line, "/clear"):
opts.Messages = []api.Message{}
if opts.System != "" {
newMessage := api.Message{Role: "system", Content: opts.System}
opts.Messages = append(opts.Messages, newMessage)
}
fmt.Println("Cleared session context")
continue
case strings.HasPrefix(line, "/set"):
args := strings.Fields(line)
if len(args) > 1 {
@ -283,13 +327,17 @@ 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 +357,23 @@ 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 +392,10 @@ 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 +405,15 @@ 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 +446,12 @@ 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 +508,13 @@ 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 +535,60 @@ 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 +608,10 @@ 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 +619,7 @@ 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 +649,7 @@ 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 +1,187 @@
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"`
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"`
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() (string, 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 {
slog.Debug(fmt.Sprintf("file = %s", fn))
if strings.HasSuffix(fn, ".safetensors") {
return &SafetensorFormat{}, nil
} else if strings.HasSuffix(fn, ".bin") {
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
}
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, int32(llm.GGUFTokenUserDefined))
}
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, int32(llm.GGUFTokenUserDefined))
}
}
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
}

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@ -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
}

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@ -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
}

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@ -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
}

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@ -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
}

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@ -1,476 +0,0 @@
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) {
t.Helper()
f, err := os.CreateTemp(t.TempDir(), "f16")
if err != nil {
t.Fatal(err)
}
defer f.Close()
if err := ConvertModel(fsys, f); err != nil {
t.Fatal(err)
}
r, err := os.Open(f.Name())
if err != nil {
t.Fatal(err)
}
t.Cleanup(func() { 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)
}
return r, 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))
}
}
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 {
t.Skipf("%s not found", p)
}
f, kv, tensors := convertFull(t, os.DirFS(p))
actual := generateResultsJSON(t, f, kv, tensors)
expectFile, err := os.Open(filepath.Join("testdata", fmt.Sprintf("%s.json", tt)))
if err != nil {
t.Fatal(err)
}
var expect map[string]string
if err := json.NewDecoder(expectFile).Decode(&expect); err != nil {
t.Fatal(err)
}
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)
}
}
})
}
}
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)
}

137
convert/gemma.go Normal file
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package convert
import (
"encoding/binary"
"fmt"
"io"
"log/slog"
"os"
"strings"
"github.com/d4l3k/go-bfloat16"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type GemmaModel struct {
ModelData
}
func gemmaLayerHandler(w io.Writer, r safetensorWriterTo, f *os.File) error {
slog.Debug(fmt.Sprintf("converting '%s'", r.t.Name))
data := make([]byte, r.end-r.start)
if err := binary.Read(f, r.bo, data); err != nil {
return err
}
tDataF32 := bfloat16.DecodeFloat32(data)
var err error
tDataF32, err = addOnes(tDataF32, int(r.t.Shape[0]))
if err != nil {
return err
}
if err := binary.Write(w, r.bo, tDataF32); err != nil {
return err
}
return nil
}
func addOnes(data []float32, vectorSize int) ([]float32, error) {
n := tensor.New(tensor.WithShape(vectorSize), tensor.WithBacking(data))
ones := tensor.Ones(tensor.Float32, vectorSize)
var err error
n, err = n.Add(ones)
if err != nil {
return []float32{}, err
}
newN, err := native.SelectF32(n, 0)
if err != nil {
return []float32{}, err
}
var fullTensor []float32
for _, v := range newN {
fullTensor = append(fullTensor, v...)
}
return fullTensor, 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)))
m.Tensors = []llm.Tensor{}
for _, l := range t {
if strings.HasSuffix(l.Name, "norm.weight") {
wt := l.WriterTo.(safetensorWriterTo)
wt.handler = gemmaLayerHandler
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) WriteGGUF() (string, 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,
}
f, err := os.CreateTemp("", "ollama-gguf")
if err != nil {
return "", err
}
defer f.Close()
mod := llm.NewGGUFV3(m.Params.ByteOrder)
if err := mod.Encode(f, kv, m.Tensors); err != nil {
return "", err
}
return f.Name(), nil
}

176
convert/llama.go Normal file
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@ -0,0 +1,176 @@
package convert
import (
"encoding/binary"
"fmt"
"io"
"log/slog"
"os"
"regexp"
"strings"
"github.com/nlpodyssey/gopickle/pytorch"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/x448/float16"
"github.com/ollama/ollama/llm"
)
type LlamaModel struct {
ModelData
}
func llamaLayerHandler(w io.Writer, r torchWriterTo) error {
slog.Debug(fmt.Sprintf("repacking layer '%s'", r.t.Name))
data := r.storage.(*pytorch.HalfStorage).Data
tData := make([]uint16, len(data))
for cnt, v := range data {
tData[cnt] = uint16(float16.Fromfloat32(v))
}
var err error
var heads uint32
if strings.Contains(r.t.Name, "attn_q") {
heads = uint32(r.params.AttentionHeads)
} else if strings.Contains(r.t.Name, "attn_k") {
heads = uint32(r.params.KeyValHeads)
if heads == 0 {
heads = uint32(r.params.AttentionHeads)
}
} else {
return fmt.Errorf("unknown layer type")
}
slog.Debug(fmt.Sprintf("heads = %d", heads))
tData, err = llamaRepack(tData, int(heads), r.t.Shape)
if err != nil {
return err
}
if err = binary.Write(w, r.bo, tData); err != nil {
return err
}
return nil
}
func llamaRepack(data []uint16, heads int, shape []uint64) ([]uint16, error) {
n := tensor.New(tensor.WithShape(int(shape[0]), int(shape[1])), tensor.WithBacking(data))
origShape := n.Shape().Clone()
// reshape the tensor and swap axes 1 and 2 to unpack the layer for gguf
if err := n.Reshape(heads, 2, origShape[0]/heads/2, origShape[1]); err != nil {
return nil, err
}
if err := n.T(0, 2, 1, 3); err != nil {
return nil, err
}
if err := n.Reshape(origShape...); err != nil {
return nil, err
}
if err := n.Transpose(); err != nil {
return nil, err
}
newN, err := native.SelectU16(n, 1)
if err != nil {
return nil, err
}
var fullTensor []uint16
for _, v := range newN {
fullTensor = append(fullTensor, v...)
}
return fullTensor, nil
}
func (m *LlamaModel) GetTensors() error {
t, err := m.Format.GetTensors(m.Path, m.Params)
if err != nil {
return err
}
m.Tensors = []llm.Tensor{}
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 {
slog.Debug(fmt.Sprintf("setting handler for: %s", l.Name))
wt := l.WriterTo.(torchWriterTo)
wt.handler = llamaLayerHandler
l.WriterTo = wt
}
m.Tensors = append(m.Tensors, l)
}
return nil
}
func (m *LlamaModel) LoadVocab() error {
var v *Vocab
var err error
slog.Debug("loading vocab")
v, err = LoadSentencePieceTokens(m.Path, m.Params)
if err != nil {
return err
}
slog.Debug("vocab loaded")
m.Vocab = v
return nil
}
func (m *LlamaModel) WriteGGUF() (string, 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.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.unknown_token_id": uint32(0),
"tokenizer.ggml.add_bos_token": true,
"tokenizer.ggml.add_eos_token": false,
}
f, err := os.CreateTemp("", "ollama-gguf")
if err != nil {
return "", err
}
defer f.Close()
mod := llm.NewGGUFV3(m.Params.ByteOrder)
if err := mod.Encode(f, kv, m.Tensors); err != nil {
return "", err
}
slog.Debug(fmt.Sprintf("gguf file = %s", f.Name()))
return f.Name(), nil
}

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convert/mistral.go Normal file
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package convert
import (
"encoding/binary"
"fmt"
"io"
"os"
"regexp"
"strings"
"github.com/d4l3k/go-bfloat16"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/x448/float16"
"github.com/ollama/ollama/llm"
)
type MistralModel struct {
ModelData
}
func mistralLayerHandler(w io.Writer, r safetensorWriterTo, f *os.File) error {
layerSize := r.end - r.start
var err error
tData := make([]uint16, layerSize/2)
if err = binary.Read(f, r.bo, tData); err != nil {
return err
}
var heads uint32
if strings.Contains(r.t.Name, "attn_q") {
heads = uint32(r.params.AttentionHeads)
} else if strings.Contains(r.t.Name, "attn_k") {
heads = uint32(r.params.KeyValHeads)
if heads == 0 {
heads = uint32(r.params.AttentionHeads)
}
} else {
return fmt.Errorf("unknown layer type")
}
tData, err = repack(tData, int(heads), r.t.Shape)
if err != nil {
return err
}
var buf []byte
for _, n := range tData {
buf = r.bo.AppendUint16(buf, n)
}
tempBuf := make([]uint16, len(tData))
tDataF32 := bfloat16.DecodeFloat32(buf)
for cnt, v := range tDataF32 {
tDataF16 := float16.Fromfloat32(v)
tempBuf[cnt] = uint16(tDataF16)
}
if err = binary.Write(w, r.bo, tempBuf); err != nil {
return err
}
return nil
}
func repack(data []uint16, heads int, shape []uint64) ([]uint16, error) {
n := tensor.New(tensor.WithShape(int(shape[0]), int(shape[1])), tensor.WithBacking(data))
origShape := n.Shape().Clone()
// reshape the tensor and swap axes 1 and 2 to unpack the layer for gguf
if err := n.Reshape(heads, 2, origShape[0]/heads/2, origShape[1]); err != nil {
return nil, err
}
if err := n.T(0, 2, 1, 3); err != nil {
return nil, err
}
if err := n.Reshape(origShape...); err != nil {
return nil, err
}
if err := n.Transpose(); err != nil {
return nil, err
}
newN, err := native.SelectU16(n, 1)
if err != nil {
return nil, err
}
var fullTensor []uint16
for _, v := range newN {
fullTensor = append(fullTensor, v...)
}
return fullTensor, nil
}
func (m *MistralModel) GetTensors() error {
t, err := m.Format.GetTensors(m.Path, m.Params)
if err != nil {
return err
}
m.Tensors = []llm.Tensor{}
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.handler = mistralLayerHandler
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() (string, 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),
}
f, err := os.CreateTemp("", "ollama-gguf")
if err != nil {
return "", err
}
defer f.Close()
mod := llm.NewGGUFV3(m.Params.ByteOrder)
if err := mod.Encode(f, kv, m.Tensors); err != nil {
return "", err
}
return f.Name(), nil
}

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convert/mixtral.go Normal file
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package convert
import (
"os"
"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
}
m.Tensors = []llm.Tensor{}
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.handler = mistralLayerHandler
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() (string, 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,
}
f, err := os.CreateTemp("", "ollama-gguf")
if err != nil {
return "", err
}
defer f.Close()
mod := llm.NewGGUFV3(m.Params.ByteOrder)
if err := mod.Encode(f, kv, m.Tensors); err != nil {
return "", err
}
return f.Name(), nil
}

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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())
}
}

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@ -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
}

317
convert/safetensors.go Normal file
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package convert
import (
"bytes"
"encoding/binary"
"encoding/json"
"fmt"
"io"
"log/slog"
"os"
"path/filepath"
"regexp"
"slices"
"github.com/d4l3k/go-bfloat16"
"github.com/mitchellh/mapstructure"
"github.com/x448/float16"
"github.com/ollama/ollama/llm"
)
type safetensorWriterTo struct {
t *llm.Tensor
params *Params
bo ByteOrder
filename string
start, end, padding uint64
handler func(w io.Writer, r safetensorWriterTo, f *os.File) error
}
type tensorMetaData struct {
Type string `mapstructure:"dtype"`
Shape []int `mapstructure:"shape"`
Offsets []int `mapstructure:"data_offsets"`
}
type SafetensorFormat struct{}
func (m *SafetensorFormat) GetTensors(dirpath string, params *Params) ([]llm.Tensor, error) {
slog.Debug("getting tensor data")
var tensors []llm.Tensor
files, err := filepath.Glob(filepath.Join(dirpath, "/model-*.safetensors"))
if err != nil {
return nil, err
}
var offset uint64
for _, f := range files {
var t []llm.Tensor
var err error
t, offset, err = m.readTensors(f, offset, params)
if err != nil {
slog.Error("%v", err)
return nil, err
}
tensors = append(tensors, t...)
}
slog.Debug(fmt.Sprintf("all tensors = %d", len(tensors)))
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 jsonSize uint64
if err := binary.Read(f, binary.LittleEndian, &jsonSize); err != nil {
return nil, 0, err
}
buf := make([]byte, jsonSize)
_, err = io.ReadFull(f, buf)
if err != nil {
return nil, 0, err
}
d := json.NewDecoder(bytes.NewBuffer(buf))
d.UseNumber()
var parsed map[string]interface{}
if err = d.Decode(&parsed); err != nil {
return nil, 0, err
}
var keys []string
for k := range parsed {
keys = append(keys, k)
}
slices.Sort(keys)
slog.Info("converting layers")
var tensors []llm.Tensor
for _, k := range keys {
vals := parsed[k].(map[string]interface{})
var data tensorMetaData
if err = mapstructure.Decode(vals, &data); err != nil {
slog.Error("couldn't decode properly")
return nil, 0, err
}
var size uint64
var kind uint32
switch len(data.Shape) {
case 0:
// metadata
continue
case 1:
// convert to float32
kind = 0
size = uint64(data.Shape[0] * 4)
case 2:
// convert to float16
kind = 1
size = uint64(data.Shape[0] * data.Shape[1] * 2)
}
ggufName, err := m.GetLayerName(k)
if err != nil {
slog.Error("%v", err)
return nil, 0, err
}
shape := []uint64{0, 0, 0, 0}
for i := range data.Shape {
shape[i] = uint64(data.Shape[i])
}
t := llm.Tensor{
Name: ggufName,
Kind: kind,
Offset: offset,
Shape: shape[:],
}
t.WriterTo = safetensorWriterTo{
t: &t,
params: params,
bo: params.ByteOrder,
filename: fn,
start: uint64(data.Offsets[0]),
end: uint64(data.Offsets[1]),
padding: 8 + jsonSize,
}
offset += size
tensors = append(tensors, t)
}
slog.Debug(fmt.Sprintf("total tensors for file = %d", len(tensors)))
slog.Debug(fmt.Sprintf("offset = %d", offset))
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
d := json.NewDecoder(f)
err = d.Decode(&params)
if 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(int64(r.padding+r.start), 0); err != nil {
return 0, err
}
// use the handler if one is present
if r.handler != nil {
return 0, r.handler(w, r, f)
}
remaining := r.end - r.start
bufSize := uint64(10240)
var finished bool
for {
data := make([]byte, min(bufSize, remaining))
b, err := io.ReadFull(f, data)
remaining -= uint64(b)
if err == io.EOF || remaining <= 0 {
finished = true
} else if err != nil {
return 0, err
}
// convert bfloat16 -> ieee float32
tDataF32 := bfloat16.DecodeFloat32(data)
switch r.t.Kind {
case 0:
if err := binary.Write(w, r.bo, tDataF32); err != nil {
return 0, err
}
case 1:
// convert float32 -> float16
tempBuf := make([]uint16, len(data)/2)
for cnt, v := range tDataF32 {
tDataF16 := float16.Fromfloat32(v)
tempBuf[cnt] = uint16(tDataF16)
}
if err := binary.Write(w, r.bo, tempBuf); err != nil {
return 0, err
}
}
if finished {
break
}
}
return 0, nil
}
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 "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",
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}

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

View File

@ -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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}

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