add batch embeddings

Fix target in gen_windows.ps1

.dockerignore

@@ -1,8 +1,9 @@
 .vscode
 ollama
 app
+macapp
 dist
 llm/llama.cpp
 .env
 .cache
-test_data
+test_data

.gitattributes

@@ -0,0 +1 @@
+llm/ext_server/* linguist-vendored

.github/ISSUE_TEMPLATE/10_bug_report.yml

@@ -0,0 +1,60 @@
+name: Bug report
+labels: [bug]
+description: Something isn't working right.
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: What is the issue?
+      description: What happened? What did you expect to happen?
+    validations:
+      required: true
+  - type: dropdown
+    id: os
+    attributes:
+      label: OS
+      description: Which operating system are you using?
+      multiple: true
+      options:
+        - Linux
+        - macOS
+        - Windows
+        - Docker
+        - WSL2
+    validations:
+      required: false
+  - type: dropdown
+    id: gpu
+    attributes:
+      label: GPU
+      description: Which GPU are you using?
+      multiple: true
+      options:
+        - Nvidia
+        - AMD
+        - Intel
+        - Apple
+        - Other
+    validations:
+      required: false
+  - type: dropdown
+    id: cpu
+    attributes:
+      label: CPU
+      description: Which CPU are you using?
+      multiple: true
+      options:
+        - Intel
+        - AMD
+        - Apple
+        - Other
+    validations:
+      required: false
+  - type: input
+    id: version
+    attributes:
+      label: Ollama version
+      description: What version of Ollama are you using? (`ollama --version`)
+      placeholder: e.g., 0.1.32
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/20_feature_request.md

@@ -0,0 +1,6 @@
+---
+name: Feature request
+about: Request a new feature
+labels: feature request
+---
+

.github/ISSUE_TEMPLATE/30_model_request.md

@@ -0,0 +1,5 @@
+---
+name: Model request
+about: Request support for a new model to be added to Ollama
+labels: model request
+---

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,8 @@
+blank_issues_enabled: true
+contact_links:
+  - name: Help
+    url: https://discord.com/invite/ollama
+    about: Please join our Discord server for help using Ollama
+  - name: Troubleshooting
+    url: https://github.com/ollama/ollama/blob/main/docs/faq.md#faq
+    about: See the FAQ for common issues and solutions

.github/workflows/latest.yaml

@@ -0,0 +1,24 @@
+name: latest
+
+on:
+  release:
+    types: [released]
+
+jobs:
+  update-latest:
+    environment: release
+    runs-on: linux
+    steps:
+      - uses: actions/checkout@v4
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ vars.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
+      - name: Tag images as latest
+        env:
+          PUSH: "1"
+        shell: bash
+        run: |
+          export "VERSION=${GITHUB_REF_NAME#v}"
+          ./scripts/tag_latest.sh

.github/workflows/release.yaml

@@ -0,0 +1,473 @@
+name: release
+
+on:
+  push:
+    tags:
+      - 'v*'
+
+jobs:
+  # Full build of the Mac assets
+  build-darwin:
+    runs-on: macos-12
+    environment: release
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set Version
+        shell: bash
+        run: |
+          echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+          echo "RELEASE_VERSION=$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)" >> $GITHUB_ENV
+      - name: key
+        env:
+          MACOS_SIGNING_KEY: ${{ secrets.MACOS_SIGNING_KEY }}
+          MACOS_SIGNING_KEY_PASSWORD: ${{ secrets.MACOS_SIGNING_KEY_PASSWORD }}
+        run: |
+          echo $MACOS_SIGNING_KEY | base64 --decode > certificate.p12
+          security create-keychain -p password build.keychain
+          security default-keychain -s build.keychain
+          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
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+      - name: Build Darwin
+        env:
+          APPLE_IDENTITY: ${{ secrets.APPLE_IDENTITY }}
+          APPLE_PASSWORD: ${{ secrets.APPLE_PASSWORD }}
+          APPLE_TEAM_ID: ${{ vars.APPLE_TEAM_ID }}
+          APPLE_ID: ${{ vars.APPLE_ID }}
+          SDKROOT: /Applications/Xcode_13.4.1.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk
+          DEVELOPER_DIR: /Applications/Xcode_13.4.1.app/Contents/Developer
+        run: |
+          ./scripts/build_darwin.sh
+
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-darwin
+          path: |
+            dist/*arwin*
+            !dist/*-cov
+
+  # Windows builds take a long time to both install the dependencies and build, so parallelize
+  # CPU generation step
+  generate-windows-cpu:
+    environment: release
+    runs-on: windows
+    env:
+      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
+      - 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"
+          go generate -x ./...
+        name: go generate
+      - uses: actions/upload-artifact@v4
+        with:
+          name: generate-windows-cpu
+          path: |
+            llm/build/**/bin/*
+            llm/build/**/*.a
+            dist/windows-amd64/**
+
+  # ROCm generation step
+  generate-windows-rocm:
+    environment: release
+    runs-on: windows
+    env:
+      KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${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
+    needs:
+      - generate-windows-cuda
+      - generate-windows-rocm
+      - generate-windows-cpu
+    env:
+      KEY_CONTAINER: ${{ vars.KEY_CONTAINER }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - uses: 'google-github-actions/auth@v2'
+        with:
+          project_id: 'ollama'
+          credentials_json: '${{ secrets.GOOGLE_SIGNING_CREDENTIALS }}'
+      - run: echo "${{ vars.OLLAMA_CERT }}" > ollama_inc.crt
+      - name: install Windows SDK 8.1 to get signtool
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading SDK"
+          Invoke-WebRequest -Uri "https://go.microsoft.com/fwlink/p/?LinkId=323507" -OutFile "${env:RUNNER_TEMP}\sdksetup.exe"
+          Start-Process "${env:RUNNER_TEMP}\sdksetup.exe" -ArgumentList @("/q") -NoNewWindow -Wait
+          write-host "Win SDK 8.1 installed"
+          gci -path 'C:\Program Files (x86)\Windows Kits\' -r -fi 'signtool.exe'
+      - name: install signing plugin
+        run: |
+          $ErrorActionPreference = "Stop"
+          write-host "downloading plugin"
+          Invoke-WebRequest -Uri "https://github.com/GoogleCloudPlatform/kms-integrations/releases/download/cng-v1.0/kmscng-1.0-windows-amd64.zip" -OutFile "${env:RUNNER_TEMP}\plugin.zip"
+          Expand-Archive -Path "${env:RUNNER_TEMP}\plugin.zip" -DestinationPath ${env:RUNNER_TEMP}\plugin\
+          write-host "Installing plugin"
+          & "${env:RUNNER_TEMP}\plugin\*\kmscng.msi" /quiet
+          write-host "plugin installed"
+      - uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+      - run: go get
+      - uses: actions/download-artifact@v4
+        with:
+          name: generate-windows-cpu
+      - uses: actions/download-artifact@v4
+        with:
+          name: generate-windows-cuda
+      - uses: actions/download-artifact@v4
+        with:
+          name: windows-cuda-deps
+      - uses: actions/download-artifact@v4
+        with:
+          name: windows-rocm-deps
+      - uses: actions/download-artifact@v4
+        with:
+          name: generate-windows-rocm
+      - run: dir llm/build
+      - run: |
+          $gopath=(get-command go).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$env:PATH"
+          $env:OLLAMA_SKIP_GENERATE="1"
+          & .\scripts\build_windows.ps1
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-windows
+          path: |
+            dist/OllamaSetup.exe
+            dist/ollama-windows-*.zip
+
+  # Linux x86 assets built using the container based build
+  build-linux-amd64:
+    environment: release
+    runs-on: linux
+    env:
+      OLLAMA_SKIP_MANIFEST_CREATE: '1'
+      BUILD_ARCH: amd64
+      PUSH: '1'
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ vars.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
+      - run: |
+          ./scripts/build_linux.sh
+          ./scripts/build_docker.sh
+          mv dist/deps/* dist/
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-linux-amd64
+          path: |
+            dist/*linux*
+            !dist/*-cov
+
+  # Linux ARM assets built using the container based build
+  # (at present, docker isn't pre-installed on arm ubunutu images)
+  build-linux-arm64:
+    environment: release
+    runs-on: linux-arm64
+    env:
+      OLLAMA_SKIP_MANIFEST_CREATE: '1'
+      BUILD_ARCH: arm64
+      PUSH: '1'
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - name: Set Version
+        shell: bash
+        run: echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+      - name: 'Install Docker'
+        run: |
+          # Add Docker's official GPG key:
+          env
+          uname -a
+          sudo apt-get update
+          sudo apt-get install -y ca-certificates curl
+          sudo install -m 0755 -d /etc/apt/keyrings
+          sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
+          sudo chmod a+r /etc/apt/keyrings/docker.asc
+
+          # Add the repository to Apt sources:
+          echo \
+            "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
+            $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
+            sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
+          sudo apt-get update
+          sudo apt-get install -y docker-ce docker-ce-cli containerd.io
+          sudo usermod -aG docker $USER
+          sudo apt-get install acl
+          sudo setfacl --modify user:$USER:rw /var/run/docker.sock
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ vars.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
+      - run: |
+          ./scripts/build_linux.sh
+          ./scripts/build_docker.sh
+      - uses: actions/upload-artifact@v4
+        with:
+          name: dist-linux-arm64
+          path: |
+            dist/*linux*
+            !dist/*-cov
+
+  # Aggregate all the assets and ship a release
+  release:
+    needs:
+      - build-darwin
+      - build-windows
+      - build-linux-amd64
+      - build-linux-arm64
+    runs-on: linux
+    environment: release
+    permissions:
+      contents: write
+    env:
+      OLLAMA_SKIP_IMAGE_BUILD: '1'
+      PUSH: '1'
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set Version
+        shell: bash
+        run: |
+          echo "VERSION=${GITHUB_REF_NAME#v}" >> $GITHUB_ENV
+          echo "RELEASE_VERSION=$(echo ${GITHUB_REF_NAME} | cut -f1 -d-)" >> $GITHUB_ENV
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ vars.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_ACCESS_TOKEN }}
+      - run: ./scripts/build_docker.sh
+      - name: Retrieve built artifact
+        uses: actions/download-artifact@v4
+        with:
+          path: dist
+          pattern: dist-*
+          merge-multiple: true
+      - run: |
+          ls -lh dist/
+          (cd dist; sha256sum * > sha256sum.txt)
+          cat dist/sha256sum.txt
+      - 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

.github/workflows/test.yaml

@@ -1,18 +1,59 @@
 name: test
 
+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.
+  #
+  # For non-PR pushes, concurrency.group needs to be unique for every distinct
+  # CI run we want to have happen. Use run_id, which in practice means all
+  # non-PR CI runs will be allowed to run without preempting each other.
+  group: ${{ github.workflow }}-$${{ github.pull_request.number || github.run_id }}
+  cancel-in-progress: true
+
 on:
   pull_request:
+    paths:
+      - '**/*'
+      - '!docs/**'
+      - '!README.md'
 
 jobs:
+  changes:
+    runs-on: ubuntu-latest
+    outputs:
+      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:
+          fetch-depth: 0
+      - id: changes
+        run: |
+          changed() {
+            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; print(any([x.startswith('$1') for x in sys.argv[1:]]))"
+          }
+
+          {
+            echo GENERATE=$(changed llm/)
+            echo GENERATE_CUDA=$(changed llm/)
+            echo GENERATE_ROCM=$(changed llm/)
+          } >>$GITHUB_OUTPUT
+
   generate:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.GENERATE == 'True' }}
     strategy:
       matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
+        os: [ubuntu-latest, macos-latest, windows-2019]
         arch: [amd64, arm64]
         exclude:
           - os: ubuntu-latest
             arch: arm64
-          - os: windows-latest
+          - os: windows-2019
             arch: arm64
     runs-on: ${{ matrix.os }}
     env:
@@ -21,15 +62,32 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-go@v5
         with:
-          go-version: '1.21'
+          go-version-file: go.mod
           cache: true
       - run: go get ./...
+      - run: |
+          $gopath=(get-command go).source | split-path -parent
+          $gccpath=(get-command gcc).source | split-path -parent
+          & "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\Common7\Tools\Launch-VsDevShell.ps1"
+          cd $env:GITHUB_WORKSPACE
+          $env:CMAKE_SYSTEM_VERSION="10.0.22621.0"
+          $env:PATH="$gopath;$gccpath;$env:PATH"
+          echo $env:PATH
+          go generate -x ./...
+        if: ${{ startsWith(matrix.os, 'windows-') }}
+        name: 'Windows Go Generate'
       - run: go generate -x ./...
+        if: ${{ ! startsWith(matrix.os, 'windows-') }}
+        name: 'Unix Go Generate'
       - uses: actions/upload-artifact@v4
         with:
           name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
-          path: llm/llama.cpp/build/**/lib/*
+          path: |
+            llm/build/**/bin/*
+            llm/build/**/*.a
   generate-cuda:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.GENERATE_CUDA == 'True' }}
     strategy:
       matrix:
         cuda-version:
@@ -46,7 +104,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-go@v4
         with:
-          go-version: '1.21'
+          go-version-file: go.mod
           cache: true
       - run: go get ./...
       - run: |
@@ -57,13 +115,16 @@ jobs:
       - uses: actions/upload-artifact@v4
         with:
           name: cuda-${{ matrix.cuda-version }}-libraries
-          path: llm/llama.cpp/build/**/lib/*
+          path: |
+            llm/build/**/bin/*
+            dist/windows-amd64/**
   generate-rocm:
+    needs: [changes]
+    if: ${{ needs.changes.outputs.GENERATE_ROCM == 'True' }}
     strategy:
       matrix:
         rocm-version:
-          - '5.7.1'
-          - '6.0'
+          - '6.0.2'
     runs-on: linux
     container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
     steps:
@@ -76,7 +137,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-go@v4
         with:
-          go-version: '1.21'
+          go-version-file: go.mod
           cache: true
       - run: go get ./...
       - run: |
@@ -87,73 +148,169 @@ jobs:
       - uses: actions/upload-artifact@v4
         with:
           name: rocm-${{ matrix.rocm-version }}-libraries
-          path: llm/llama.cpp/build/**/lib/*
+          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:
       matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
+        os: [ubuntu-latest, macos-latest, windows-2019]
         arch: [amd64, arm64]
         exclude:
           - os: ubuntu-latest
             arch: arm64
-          - os: windows-latest
+          - os: windows-2019
             arch: arm64
           - os: macos-latest
             arch: amd64
     runs-on: ${{ matrix.os }}
     env:
       GOARCH: ${{ matrix.arch }}
-      CGO_ENABLED: "1"
+      CGO_ENABLED: '1'
     steps:
       - uses: actions/checkout@v4
         with:
           submodules: recursive
       - uses: actions/setup-go@v5
         with:
-          go-version: '1.21'
+          go-version-file: go.mod
           cache: false
       - run: |
-          mkdir -p llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/
-          touch llm/llama.cpp/build/linux/${{ matrix.arch }}/stub/lib/stub.so
+          case ${{ matrix.arch }} in
+            amd64) echo ARCH=x86_64 ;;
+            arm64) echo ARCH=arm64 ;;
+          esac >>$GITHUB_ENV
+        shell: bash
+      - run: |
+          mkdir -p llm/build/linux/$ARCH/stub/bin
+          touch llm/build/linux/$ARCH/stub/bin/ollama_llama_server
         if: ${{ startsWith(matrix.os, 'ubuntu-') }}
       - run: |
-          mkdir -p llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/
-          touch llm/llama.cpp/build/darwin/${{ matrix.arch }}/stub/lib/stub.dylib
-          touch llm/llama.cpp/ggml-metal.metal
+          mkdir -p llm/build/darwin/$ARCH/stub/bin
+          touch llm/build/darwin/$ARCH/stub/bin/ollama_llama_server
         if: ${{ startsWith(matrix.os, 'macos-') }}
-      - run: |
-          mkdir -p llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/
-          touch llm/llama.cpp/build/windows/${{ matrix.arch }}/stub/lib/stub.dll
-        if: ${{ startsWith(matrix.os, 'windows-') }}
-      - uses: golangci/golangci-lint-action@v3
+      - uses: golangci/golangci-lint-action@v4
+        with:
+          args: --timeout 8m0s -v
   test:
-    needs: generate
     strategy:
       matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
+        os: [ubuntu-latest, macos-latest, windows-2019]
         arch: [amd64]
         exclude:
           - os: ubuntu-latest
             arch: arm64
-          - os: windows-latest
+          - os: windows-2019
             arch: arm64
     runs-on: ${{ matrix.os }}
     env:
       GOARCH: ${{ matrix.arch }}
-      CGO_ENABLED: "1"
+      CGO_ENABLED: '1'
+      OLLAMA_CPU_TARGET: 'static'
     steps:
       - uses: actions/checkout@v4
         with:
           submodules: recursive
       - uses: actions/setup-go@v5
         with:
-          go-version: '1.21'
+          go-version-file: go.mod
           cache: true
-      - run: go get
-      - uses: actions/download-artifact@v4
-        with:
-          name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
-          path: llm/llama.cpp/build
+      - run: |
+          case ${{ matrix.arch }} in
+            amd64) echo ARCH=x86_64 ;;
+            arm64) echo ARCH=arm64 ;;
+          esac >>$GITHUB_ENV
+        shell: bash
+      - run: |
+          mkdir -p llm/build/linux/$ARCH/stub/bin
+          touch llm/build/linux/$ARCH/stub/bin/ollama_llama_server
+        if: ${{ startsWith(matrix.os, 'ubuntu-') }}
+      - run: |
+          mkdir -p llm/build/darwin/$ARCH/stub/bin
+          touch llm/build/darwin/$ARCH/stub/bin/ollama_llama_server
+        if: ${{ startsWith(matrix.os, 'macos-') }}
+        shell: bash
+      - run: go generate ./...
       - run: go build
       - run: go test -v ./...
       - uses: actions/upload-artifact@v4

.gitignore

@@ -10,4 +10,5 @@ ggml-metal.metal
 *.exe
 .idea
 test_data
-*.crt
+*.crt
+llm/build

.golangci.yaml

@@ -15,13 +15,3 @@ linters:
     - misspell
     - nilerr
     - unused
-linters-settings:
-  errcheck:
-    # exclude the following functions since we don't generally
-    # need to be concerned with the returned errors
-    exclude-functions:
-      - encoding/binary.Read
-      - (*os.File).Seek
-      - (*bufio.Writer).WriteString
-      - (*github.com/spf13/pflag.FlagSet).Set
-      - (*github.com/jmorganca/ollama/llm.readSeekOffset).Seek

Dockerfile

@@ -1,6 +1,8 @@
-ARG GOLANG_VERSION=1.21.3
+ARG GOLANG_VERSION=1.22.1
 ARG CMAKE_VERSION=3.22.1
+# this CUDA_VERSION corresponds with the one specified in docs/gpu.md
 ARG CUDA_VERSION=11.3.1
+ARG ROCM_VERSION=6.0.2
 
 # Copy the minimal context we need to run the generate scripts
 FROM scratch AS llm-code
@@ -13,44 +15,40 @@ ARG CMAKE_VERSION
 COPY ./scripts/rh_linux_deps.sh /
 RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
 ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
-COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
-WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+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_CPU_GENERATE=1 sh gen_linux.sh
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
 
 FROM --platform=linux/arm64 nvidia/cuda:$CUDA_VERSION-devel-rockylinux8 AS cuda-build-arm64
 ARG CMAKE_VERSION
 COPY ./scripts/rh_linux_deps.sh /
 RUN CMAKE_VERSION=${CMAKE_VERSION} sh /rh_linux_deps.sh
 ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
-COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
-WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+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_CPU_GENERATE=1 sh gen_linux.sh
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
 
-FROM --platform=linux/amd64 rocm/dev-centos-7:5.7.1-complete AS rocm-5-build-amd64
+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/jmorganca/ollama/
-WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
+WORKDIR /go/src/github.com/ollama/ollama/llm/generate
 ARG CGO_CFLAGS
 ARG AMDGPU_TARGETS
-RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
+RUN mkdir /tmp/scratch && \
+    for dep in $(zcat /go/src/github.com/ollama/ollama/llm/build/linux/x86_64/rocm*/bin/deps.txt.gz) ; do \
+        cp ${dep} /tmp/scratch/ || exit 1 ; \
+    done && \
+    (cd /opt/rocm/lib && tar cf - rocblas/library) | (cd /tmp/scratch/ && tar xf - ) && \
+    mkdir -p /go/src/github.com/ollama/ollama/dist/deps/ && \
+    (cd /tmp/scratch/ && tar czvf /go/src/github.com/ollama/ollama/dist/deps/ollama-linux-amd64-rocm.tgz . )
 
-FROM --platform=linux/amd64 rocm/dev-centos-7:6.0-complete AS rocm-6-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/jmorganca/ollama/
-WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
-ARG CGO_CFLAGS
-ARG AMDGPU_TARGETS
-RUN OLLAMA_SKIP_CPU_GENERATE=1 sh gen_linux.sh
 
 FROM --platform=linux/amd64 centos:7 AS cpu-builder-amd64
 ARG CMAKE_VERSION
@@ -58,68 +56,76 @@ ARG GOLANG_VERSION
 COPY ./scripts/rh_linux_deps.sh /
 RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
 ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
-COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
 ARG OLLAMA_CUSTOM_CPU_DEFS
 ARG CGO_CFLAGS
-WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
+WORKDIR /go/src/github.com/ollama/ollama/llm/generate
 
+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_CPU_TARGET="cpu" sh gen_linux.sh
+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_CPU_TARGET="cpu_avx" sh gen_linux.sh
+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_CPU_TARGET="cpu_avx2" sh gen_linux.sh
+RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
 
-FROM --platform=linux/arm64 centos:7 AS cpu-build-arm64
+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/devtoolset-10/root/usr/bin:$PATH
-COPY --from=llm-code / /go/src/github.com/jmorganca/ollama/
-WORKDIR /go/src/github.com/jmorganca/ollama/llm/generate
-# Note, we only build the "base" CPU variant on arm since avx/avx2 are x86 features
+COPY --from=llm-code / /go/src/github.com/ollama/ollama/
 ARG OLLAMA_CUSTOM_CPU_DEFS
 ARG CGO_CFLAGS
-RUN OLLAMA_CPU_TARGET="cpu" sh gen_linux.sh
+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
-WORKDIR /go/src/github.com/jmorganca/ollama
+WORKDIR /go/src/github.com/ollama/ollama
 COPY . .
-COPY --from=cpu_avx-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
-COPY --from=cpu_avx2-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
-COPY --from=cuda-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
-COPY --from=rocm-5-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
-COPY --from=rocm-6-build-amd64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
+COPY --from=static-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cpu_avx-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cpu_avx2-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cuda-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=rocm-build-amd64 /go/src/github.com/ollama/ollama/dist/deps/ ./dist/deps/
 ARG GOFLAGS
 ARG CGO_CFLAGS
-RUN go build .
+RUN go build -trimpath .
 
 # 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/jmorganca/ollama
+WORKDIR /go/src/github.com/ollama/ollama
 COPY . .
-COPY --from=cuda-build-arm64 /go/src/github.com/jmorganca/ollama/llm/llama.cpp/build/linux/ llm/llama.cpp/build/linux/
+COPY --from=static-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
+COPY --from=cuda-build-arm64 /go/src/github.com/ollama/ollama/llm/build/linux/ llm/build/linux/
 ARG GOFLAGS
 ARG CGO_CFLAGS
-RUN go build .
+RUN go build -trimpath .
 
 # 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/jmorganca/ollama/ollama /bin/ollama
+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/jmorganca/ollama/ollama /bin/ollama
+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-7:5.7.1-complete as runtime-rocm
+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/jmorganca/ollama/ollama /bin/ollama
+COPY --from=build-amd64 /go/src/github.com/ollama/ollama/ollama /bin/ollama
 EXPOSE 11434
 ENV OLLAMA_HOST 0.0.0.0
 
@@ -132,6 +138,7 @@ ENV OLLAMA_HOST 0.0.0.0
 ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
 ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
+ENV NVIDIA_VISIBLE_DEVICES=all
 
 ENTRYPOINT ["/bin/ollama"]
 CMD ["serve"]

README.md

@@ -1,5 +1,5 @@
 <div align="center">
-  <img alt="ollama" height="200px" src="https://github.com/jmorganca/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
@@ -22,7 +22,7 @@ Get up and running with large language models locally.
 curl -fsSL https://ollama.com/install.sh | sh
 ```
 
-[Manual install instructions](https://github.com/jmorganca/ollama/blob/main/docs/linux.md)
+[Manual install instructions](https://github.com/ollama/ollama/blob/main/docs/linux.md)
 
 ### Docker
 
@@ -35,10 +35,10 @@ The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `olla
 
 ## Quickstart
 
-To run and chat with [Llama 2](https://ollama.com/library/llama2):
+To run and chat with [Llama 3](https://ollama.com/library/llama3):
 
 ```
-ollama run llama2
+ollama run llama3
 ```
 
 ## Model library
@@ -49,19 +49,18 @@ Here are some example models that can be downloaded:
 
 | Model              | Parameters | Size  | Download                       |
 | ------------------ | ---------- | ----- | ------------------------------ |
-| Llama 2            | 7B         | 3.8GB | `ollama run llama2`            |
+| 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`           |
-| Dolphin Phi        | 2.7B       | 1.6GB | `ollama run dolphin-phi`       |
-| Phi-2              | 2.7B       | 1.7GB | `ollama run phi`               |
 | 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` |
-| Llama 2 13B        | 13B        | 7.3GB | `ollama run llama2:13b`        |
-| Llama 2 70B        | 70B        | 39GB  | `ollama run llama2:70b`        |
-| Orca Mini          | 3B         | 1.9GB | `ollama run orca-mini`         |
-| Vicuna             | 7B         | 3.8GB | `ollama run vicuna`            |
 | 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.
 
@@ -95,16 +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 `llama2` model:
+Models from the Ollama library can be customized with a prompt. For example, to customize the `llama3` model:
 
 ```
-ollama pull llama2
+ollama pull llama3
 ```
 
 Create a `Modelfile`:
 
 ```
-FROM llama2
+FROM llama3
 
 # set the temperature to 1 [higher is more creative, lower is more coherent]
 PARAMETER temperature 1
@@ -139,7 +138,7 @@ ollama create mymodel -f ./Modelfile
 ### Pull a model
 
 ```
-ollama pull llama2
+ollama pull llama3
 ```
 
 > This command can also be used to update a local model. Only the diff will be pulled.
@@ -147,13 +146,13 @@ ollama pull llama2
 ### Remove a model
 
 ```
-ollama rm llama2
+ollama rm llama3
 ```
 
 ### Copy a model
 
 ```
-ollama cp llama2 my-llama2
+ollama cp llama3 my-model
 ```
 
 ### Multiline input
@@ -177,7 +176,7 @@ The image features a yellow smiley face, which is likely the central focus of th
 ### Pass in prompt as arguments
 
 ```
-$ ollama run llama2 "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.
 ```
 
@@ -211,7 +210,7 @@ Then build the binary:
 go build .
 ```
 
-More detailed instructions can be found in the [developer guide](https://github.com/jmorganca/ollama/blob/main/docs/development.md)
+More detailed instructions can be found in the [developer guide](https://github.com/ollama/ollama/blob/main/docs/development.md)
 
 ### Running local builds
 
@@ -224,7 +223,7 @@ Next, start the server:
 Finally, in a separate shell, run a model:
 
 ```
-./ollama run llama2
+./ollama run llama3
 ```
 
 ## REST API
@@ -235,7 +234,7 @@ Ollama has a REST API for running and managing models.
 
 ```
 curl http://localhost:11434/api/generate -d '{
-  "model": "llama2",
+  "model": "llama3",
   "prompt":"Why is the sky blue?"
 }'
 ```
@@ -244,7 +243,7 @@ curl http://localhost:11434/api/generate -d '{
 
 ```
 curl http://localhost:11434/api/chat -d '{
-  "model": "mistral",
+  "model": "llama3",
   "messages": [
     { "role": "user", "content": "why is the sky blue?" }
   ]
@@ -257,20 +256,45 @@ See the [API documentation](./docs/api.md) for all endpoints.
 
 ### Web & Desktop
 
+- [Open WebUI](https://github.com/open-webui/open-webui)
+- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
+- [Lollms-Webui](https://github.com/ParisNeo/lollms-webui)
+- [LibreChat](https://github.com/danny-avila/LibreChat)
 - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
 - [HTML UI](https://github.com/rtcfirefly/ollama-ui)
+- [Saddle](https://github.com/jikkuatwork/saddle)
 - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
+- [Chatbot UI v2](https://github.com/mckaywrigley/chatbot-ui)
 - [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
 - [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui)
-- [Open WebUI](https://github.com/open-webui/open-webui)
 - [Ollamac](https://github.com/kevinhermawan/Ollamac)
-- [big-AGI](https://github.com/enricoros/big-agi/blob/main/docs/config-ollama.md)
+- [big-AGI](https://github.com/enricoros/big-AGI/blob/main/docs/config-local-ollama.md)
 - [Cheshire Cat assistant framework](https://github.com/cheshire-cat-ai/core)
 - [Amica](https://github.com/semperai/amica)
 - [chatd](https://github.com/BruceMacD/chatd)
 - [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI)
+- [Dify.AI](https://github.com/langgenius/dify)
 - [MindMac](https://mindmac.app)
 - [NextJS Web Interface for Ollama](https://github.com/jakobhoeg/nextjs-ollama-llm-ui)
+- [Msty](https://msty.app)
+- [Chatbox](https://github.com/Bin-Huang/Chatbox)
+- [WinForm Ollama Copilot](https://github.com/tgraupmann/WinForm_Ollama_Copilot)
+- [NextChat](https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web) with [Get Started Doc](https://docs.nextchat.dev/models/ollama)
+- [Alpaca WebUI](https://github.com/mmo80/alpaca-webui)
+- [OllamaGUI](https://github.com/enoch1118/ollamaGUI)
+- [OpenAOE](https://github.com/InternLM/OpenAOE)
+- [Odin Runes](https://github.com/leonid20000/OdinRunes)
+- [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: 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: Local Chat with multiples PDFs using Ollama and RAG.](https://github.com/datvodinh/rag-chatbot.git)
 
 ### Terminal
 
@@ -279,18 +303,25 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Emacs client](https://github.com/zweifisch/ollama)
 - [gen.nvim](https://github.com/David-Kunz/gen.nvim)
 - [ollama.nvim](https://github.com/nomnivore/ollama.nvim)
+- [ollero.nvim](https://github.com/marco-souza/ollero.nvim)
 - [ollama-chat.nvim](https://github.com/gerazov/ollama-chat.nvim)
 - [ogpt.nvim](https://github.com/huynle/ogpt.nvim)
 - [gptel Emacs client](https://github.com/karthink/gptel)
 - [Oatmeal](https://github.com/dustinblackman/oatmeal)
 - [cmdh](https://github.com/pgibler/cmdh)
+- [ooo](https://github.com/npahlfer/ooo)
+- [shell-pilot](https://github.com/reid41/shell-pilot)
 - [tenere](https://github.com/pythops/tenere)
 - [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/).
+- [typechat-cli](https://github.com/anaisbetts/typechat-cli)
 - [ShellOracle](https://github.com/djcopley/ShellOracle)
+- [tlm](https://github.com/yusufcanb/tlm)
+- [podman-ollama](https://github.com/ericcurtin/podman-ollama)
 
 ### Database
 
-- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md)
+- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md) (Connects Ollama models with nearly 200 data platforms and apps)
+- [chromem-go](https://github.com/philippgille/chromem-go/blob/v0.5.0/embed_ollama.go) with [example](https://github.com/philippgille/chromem-go/tree/v0.5.0/examples/rag-wikipedia-ollama)
 
 ### Package managers
 
@@ -301,8 +332,8 @@ See the [API documentation](./docs/api.md) for all endpoints.
 
 - [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)
 - [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
-- [LangChain4j](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-ollama)
 - [LiteLLM](https://github.com/BerriAI/litellm)
 - [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
 - [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
@@ -315,8 +346,11 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [LangChainDart](https://github.com/davidmigloz/langchain_dart)
 - [Semantic Kernel - Python](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/ai/ollama)
 - [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-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/)
 
 ### Mobile
 
@@ -330,6 +364,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Continue](https://github.com/continuedev/continue)
 - [Obsidian Ollama plugin](https://github.com/hinterdupfinger/obsidian-ollama)
 - [Logseq Ollama plugin](https://github.com/omagdy7/ollama-logseq)
+- [NotesOllama](https://github.com/andersrex/notesollama) (Apple Notes Ollama plugin)
 - [Dagger Chatbot](https://github.com/samalba/dagger-chatbot)
 - [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot)
 - [Ollama Telegram Bot](https://github.com/ruecat/ollama-telegram)
@@ -337,6 +372,16 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [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)
 - [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 HuggingFace)
+- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)
+- [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)
+
+### Supported backends 
+- [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov. 

api/client.go

@@ -1,3 +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 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.
 package api
 
 import (
@@ -5,7 +11,6 @@ import (
 	"bytes"
 	"context"
 	"encoding/json"
-	"errors"
 	"fmt"
 	"io"
 	"net"
@@ -15,13 +20,15 @@ import (
 	"runtime"
 	"strings"
 
-	"github.com/jmorganca/ollama/format"
-	"github.com/jmorganca/ollama/version"
+	"github.com/ollama/ollama/format"
+	"github.com/ollama/ollama/version"
 )
 
+// Client encapsulates client state for interacting with the ollama
+// service. Use [ClientFromEnvironment] to create new Clients.
 type Client struct {
 	base *url.URL
-	http http.Client
+	http *http.Client
 }
 
 func checkError(resp *http.Response, body []byte) error {
@@ -40,6 +47,15 @@ func checkError(resp *http.Response, body []byte) error {
 	return apiError
 }
 
+// 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 listenting. The format of this variable
+// is:
+//
+//	<scheme>://<host>:<port>
+//
+// If the variable is not specified, a default ollama host and port will be
+// used.
 func ClientFromEnvironment() (*Client, error) {
 	defaultPort := "11434"
 
@@ -66,30 +82,20 @@ func ClientFromEnvironment() (*Client, error) {
 		}
 	}
 
-	client := Client{
+	return &Client{
 		base: &url.URL{
 			Scheme: scheme,
 			Host:   net.JoinHostPort(host, port),
 		},
-	}
+		http: http.DefaultClient,
+	}, nil
+}
 
-	mockRequest, err := http.NewRequest(http.MethodHead, client.base.String(), nil)
-	if err != nil {
-		return nil, err
+func NewClient(base *url.URL, http *http.Client) *Client {
+	return &Client{
+		base: base,
+		http: http,
 	}
-
-	proxyURL, err := http.ProxyFromEnvironment(mockRequest)
-	if err != nil {
-		return nil, err
-	}
-
-	client.http = http.Client{
-		Transport: &http.Transport{
-			Proxy: http.ProxyURL(proxyURL),
-		},
-	}
-
-	return &client, nil
 }
 
 func (c *Client) do(ctx context.Context, method, path string, reqData, respData any) error {
@@ -208,8 +214,14 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
 	return nil
 }
 
+// GenerateResponseFunc is a function that [Client.Generate] invokes every time
+// a response is received from the service. If this function returns an error,
+// [Client.Generate] will stop generating and return this error.
 type GenerateResponseFunc func(GenerateResponse) error
 
+// Generate generates a response for a given prompt. The req parameter should
+// be populated with prompt details. fn is called for each response (there may
+// be multiple responses, e.g. in case streaming is enabled).
 func (c *Client) Generate(ctx context.Context, req *GenerateRequest, fn GenerateResponseFunc) error {
 	return c.stream(ctx, http.MethodPost, "/api/generate", req, func(bts []byte) error {
 		var resp GenerateResponse
@@ -221,8 +233,15 @@ func (c *Client) Generate(ctx context.Context, req *GenerateRequest, fn Generate
 	})
 }
 
+// ChatResponseFunc is a function that [Client.Chat] invokes every time
+// a response is received from the service. If this function returns an error,
+// [Client.Chat] will stop generating and return this error.
 type ChatResponseFunc func(ChatResponse) error
 
+// Chat generates the next message in a chat. [ChatRequest] may contain a
+// sequence of messages which can be used to maintain chat history with a model.
+// fn is called for each response (there may be multiple responses, e.g. if case
+// streaming is enabled).
 func (c *Client) Chat(ctx context.Context, req *ChatRequest, fn ChatResponseFunc) error {
 	return c.stream(ctx, http.MethodPost, "/api/chat", req, func(bts []byte) error {
 		var resp ChatResponse
@@ -234,8 +253,14 @@ func (c *Client) Chat(ctx context.Context, req *ChatRequest, fn ChatResponseFunc
 	})
 }
 
+// PullProgressFunc is a function that [Client.Pull] invokes every time there
+// is progress with a "pull" request sent to the service. If this function
+// returns an error, [Client.Pull] will stop the process and return this error.
 type PullProgressFunc func(ProgressResponse) error
 
+// Pull downloads a model from the ollama library. fn is called each time
+// progress is made on the request and can be used to display a progress bar,
+// etc.
 func (c *Client) Pull(ctx context.Context, req *PullRequest, fn PullProgressFunc) error {
 	return c.stream(ctx, http.MethodPost, "/api/pull", req, func(bts []byte) error {
 		var resp ProgressResponse
@@ -318,18 +343,7 @@ func (c *Client) Embeddings(ctx context.Context, req *EmbeddingRequest) (*Embedd
 }
 
 func (c *Client) CreateBlob(ctx context.Context, digest string, r io.Reader) error {
-	if err := c.do(ctx, http.MethodHead, fmt.Sprintf("/api/blobs/%s", digest), nil, nil); err != nil {
-		var statusError StatusError
-		if !errors.As(err, &statusError) || statusError.StatusCode != http.StatusNotFound {
-			return err
-		}
-
-		if err := c.do(ctx, http.MethodPost, fmt.Sprintf("/api/blobs/%s", digest), r, nil); err != nil {
-			return err
-		}
-	}
-
-	return nil
+	return c.do(ctx, http.MethodPost, fmt.Sprintf("/api/blobs/%s", digest), r, nil)
 }
 
 func (c *Client) Version(ctx context.Context) (string, error) {

api/types.go

@@ -2,6 +2,7 @@ package api
 
 import (
 	"encoding/json"
+	"errors"
 	"fmt"
 	"math"
 	"os"
@@ -33,18 +34,46 @@ func (e StatusError) Error() string {
 
 type ImageData []byte
 
+// GenerateRequest describes a request sent by [Client.Generate]. While you
+// have to specify the Model and Prompt fields, all the other fields have
+// reasonable defaults for basic uses.
 type GenerateRequest struct {
-	Model     string      `json:"model"`
-	Prompt    string      `json:"prompt"`
-	System    string      `json:"system"`
-	Template  string      `json:"template"`
-	Context   []int       `json:"context,omitempty"`
-	Stream    *bool       `json:"stream,omitempty"`
-	Raw       bool        `json:"raw,omitempty"`
-	Format    string      `json:"format"`
-	KeepAlive *Duration   `json:"keep_alive,omitempty"`
-	Images    []ImageData `json:"images,omitempty"`
+	// Model is the model name; it should be a name familiar to Ollama from
+	// the library at https://ollama.com/library
+	Model string `json:"model"`
 
+	// Prompt is the textual prompt to send to the model.
+	Prompt string `json:"prompt"`
+
+	// System overrides the model's default system message/prompt.
+	System string `json:"system"`
+
+	// Template overrides the model's default prompt template.
+	Template string `json:"template"`
+
+	// Context is the context parameter returned from a previous call to
+	// 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.
+	Stream *bool `json:"stream,omitempty"`
+
+	// Raw set to true means that no formatting will be applied to the prompt.
+	Raw bool `json:"raw,omitempty"`
+
+	// Format specifies the format to return a response in.
+	Format string `json:"format"`
+
+	// KeepAlive controls how long the model will stay loaded in memory following
+	// this request.
+	KeepAlive *Duration `json:"keep_alive,omitempty"`
+
+	// Images is an optional list of base64-encoded images accompanying this
+	// request, for multimodal models.
+	Images []ImageData `json:"images,omitempty"`
+
+	// Options lists model-specific options. For example, temperature can be
+	// set through this field, if the model supports it.
 	Options map[string]interface{} `json:"options"`
 }
 
@@ -83,7 +112,7 @@ type Metrics struct {
 	EvalDuration       time.Duration `json:"eval_duration,omitempty"`
 }
 
-// Options specfied in GenerateRequest, if you add a new option here add it to the API docs also
+// Options specified in GenerateRequest, if you add a new option here add it to the API docs also
 type Options struct {
 	Runner
 
@@ -109,41 +138,46 @@ type Options struct {
 
 // Runner options which must be set when the model is loaded into memory
 type Runner struct {
-	UseNUMA            bool    `json:"numa,omitempty"`
-	NumCtx             int     `json:"num_ctx,omitempty"`
-	NumBatch           int     `json:"num_batch,omitempty"`
-	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"`
-	EmbeddingOnly      bool    `json:"embedding_only,omitempty"`
-	RopeFrequencyBase  float32 `json:"rope_frequency_base,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"`
-	NumThread          int     `json:"num_thread,omitempty"`
 }
 
 type EmbeddingRequest struct {
-	Model     string    `json:"model"`
-	Prompt    string    `json:"prompt"`
-	KeepAlive *Duration `json:"keep_alive,omitempty"`
+	Model       string    `json:"model"`
+	Prompt      string    `json:"prompt,omitempty"`
+	PromptBatch []string  `json:"prompt_batch,omitempty"`
+	KeepAlive   *Duration `json:"keep_alive,omitempty"`
 
 	Options map[string]interface{} `json:"options"`
 }
 
 type EmbeddingResponse struct {
-	Embedding []float64 `json:"embedding"`
+	Embedding      []float64   `json:"embedding,omitempty"`
+	EmbeddingBatch [][]float64 `json:"embedding_batch,omitempty"`
 }
 
 type CreateRequest struct {
-	Model     string `json:"model"`
-	Path      string `json:"path"`
-	Modelfile string `json:"modelfile"`
-	Stream    *bool  `json:"stream,omitempty"`
+	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"`
@@ -276,7 +310,7 @@ func (m *Metrics) Summary() {
 	}
 }
 
-var ErrInvalidOpts = fmt.Errorf("invalid options")
+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
@@ -364,8 +398,10 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
 func DefaultOptions() Options {
 	return Options{
 		// options set on request to runner
-		NumPredict:       -1,
-		NumKeep:          0,
+		NumPredict: -1,
+
+		// set a minimal num_keep to avoid issues on context shifts
+		NumKeep:          4,
 		Temperature:      0.8,
 		TopK:             40,
 		TopP:             0.9,
@@ -383,19 +419,16 @@ func DefaultOptions() Options {
 
 		Runner: Runner{
 			// options set when the model is loaded
-			NumCtx:             2048,
-			RopeFrequencyBase:  10000.0,
-			RopeFrequencyScale: 1.0,
-			NumBatch:           512,
-			NumGPU:             -1, // -1 here indicates that NumGPU should be set dynamically
-			NumGQA:             1,
-			NumThread:          0, // let the runtime decide
-			LowVRAM:            false,
-			F16KV:              true,
-			UseMLock:           false,
-			UseMMap:            true,
-			UseNUMA:            false,
-			EmbeddingOnly:      true,
+			NumCtx:    2048,
+			NumBatch:  512,
+			NumGPU:    -1, // -1 here indicates that NumGPU should be set dynamically
+			NumGQA:    1,
+			NumThread: 0, // let the runtime decide
+			LowVRAM:   false,
+			F16KV:     true,
+			UseMLock:  false,
+			UseMMap:   true,
+			UseNUMA:   false,
 		},
 	}
 }

api/types_test.go

@@ -0,0 +1,50 @@
+package api
+
+import (
+	"encoding/json"
+	"math"
+	"testing"
+	"time"
+
+	"github.com/stretchr/testify/assert"
+	"github.com/stretchr/testify/require"
+)
+
+func TestKeepAliveParsingFromJSON(t *testing.T) {
+	tests := []struct {
+		name string
+		req  string
+		exp  *Duration
+	}{
+		{
+			name: "Positive Integer",
+			req:  `{ "keep_alive": 42 }`,
+			exp:  &Duration{42 * time.Second},
+		},
+		{
+			name: "Positive Integer String",
+			req:  `{ "keep_alive": "42m" }`,
+			exp:  &Duration{42 * time.Minute},
+		},
+		{
+			name: "Negative Integer",
+			req:  `{ "keep_alive": -1 }`,
+			exp:  &Duration{math.MaxInt64},
+		},
+		{
+			name: "Negative Integer String",
+			req:  `{ "keep_alive": "-1m" }`,
+			exp:  &Duration{math.MaxInt64},
+		},
+	}
+
+	for _, test := range tests {
+		t.Run(test.name, func(t *testing.T) {
+			var dec ChatRequest
+			err := json.Unmarshal([]byte(test.req), &dec)
+			require.NoError(t, err)
+
+			assert.Equal(t, test.exp, dec.KeepAlive)
+		})
+	}
+}

app/lifecycle/lifecycle.go

@@ -9,8 +9,8 @@ import (
 	"os/signal"
 	"syscall"
 
-	"github.com/jmorganca/ollama/app/store"
-	"github.com/jmorganca/ollama/app/tray"
+	"github.com/ollama/ollama/app/store"
+	"github.com/ollama/ollama/app/tray"
 )
 
 func Run() {

app/lifecycle/server.go

@@ -11,7 +11,7 @@ import (
 	"path/filepath"
 	"time"
 
-	"github.com/jmorganca/ollama/api"
+	"github.com/ollama/ollama/api"
 )
 
 func getCLIFullPath(command string) string {
@@ -83,6 +83,38 @@ func SpawnServer(ctx context.Context, command string) (chan int, error) {
 		io.Copy(logFile, stderr) //nolint:errcheck
 	}()
 
+	// Re-wire context done behavior to attempt a graceful shutdown of the server
+	cmd.Cancel = func() error {
+		if cmd.Process != nil {
+			err := terminate(cmd)
+			if err != nil {
+				slog.Warn("error trying to gracefully terminate server", "err", err)
+				return cmd.Process.Kill()
+			}
+
+			tick := time.NewTicker(10 * time.Millisecond)
+			defer tick.Stop()
+
+			for {
+				select {
+				case <-tick.C:
+					exited, err := isProcessExited(cmd.Process.Pid)
+					if err != nil {
+						return err
+					}
+
+					if exited {
+						return nil
+					}
+				case <-time.After(5 * time.Second):
+					slog.Warn("graceful server shutdown timeout, killing", "pid", cmd.Process.Pid)
+					return cmd.Process.Kill()
+				}
+			}
+		}
+		return nil
+	}
+
 	// run the command and wait for it to finish
 	if err := cmd.Start(); err != nil {
 		return done, fmt.Errorf("failed to start server %w", err)
@@ -105,7 +137,7 @@ func SpawnServer(ctx context.Context, command string) (chan int, error) {
 
 			select {
 			case <-ctx.Done():
-				slog.Debug(fmt.Sprintf("server shutdown with exit code %d", code))
+				slog.Info(fmt.Sprintf("server shutdown with exit code %d", code))
 				done <- code
 				return
 			default:

app/lifecycle/server_unix.go

@@ -4,9 +4,35 @@ package lifecycle
 
 import (
 	"context"
+	"errors"
+	"fmt"
+	"os"
 	"os/exec"
+	"syscall"
 )
 
 func getCmd(ctx context.Context, cmd string) *exec.Cmd {
 	return exec.CommandContext(ctx, cmd, "serve")
 }
+
+func terminate(cmd *exec.Cmd) error {
+	return cmd.Process.Signal(os.Interrupt)
+}
+
+func isProcessExited(pid int) (bool, error) {
+	proc, err := os.FindProcess(pid)
+	if err != nil {
+		return false, fmt.Errorf("failed to find process: %v", err)
+	}
+
+	err = proc.Signal(syscall.Signal(0))
+	if err != nil {
+		if errors.Is(err, os.ErrProcessDone) || errors.Is(err, syscall.ESRCH) {
+			return true, nil
+		}
+
+		return false, fmt.Errorf("error signaling process: %v", err)
+	}
+
+	return false, nil
+}

app/lifecycle/server_windows.go

@@ -2,12 +2,88 @@ package lifecycle
 
 import (
 	"context"
+	"fmt"
 	"os/exec"
 	"syscall"
+
+	"golang.org/x/sys/windows"
 )
 
 func getCmd(ctx context.Context, exePath string) *exec.Cmd {
 	cmd := exec.CommandContext(ctx, exePath, "serve")
-	cmd.SysProcAttr = &syscall.SysProcAttr{HideWindow: true, CreationFlags: 0x08000000}
+	cmd.SysProcAttr = &syscall.SysProcAttr{
+		HideWindow:    true,
+		CreationFlags: windows.CREATE_NEW_PROCESS_GROUP,
+	}
+
 	return cmd
 }
+
+func terminate(cmd *exec.Cmd) error {
+	dll, err := windows.LoadDLL("kernel32.dll")
+	if err != nil {
+		return err
+	}
+	defer dll.Release() // nolint: errcheck
+
+	pid := cmd.Process.Pid
+
+	f, err := dll.FindProc("AttachConsole")
+	if err != nil {
+		return err
+	}
+
+	r1, _, err := f.Call(uintptr(pid))
+	if r1 == 0 && err != syscall.ERROR_ACCESS_DENIED {
+		return err
+	}
+
+	f, err = dll.FindProc("SetConsoleCtrlHandler")
+	if err != nil {
+		return err
+	}
+
+	r1, _, err = f.Call(0, 1)
+	if r1 == 0 {
+		return err
+	}
+
+	f, err = dll.FindProc("GenerateConsoleCtrlEvent")
+	if err != nil {
+		return err
+	}
+
+	r1, _, err = f.Call(windows.CTRL_BREAK_EVENT, uintptr(pid))
+	if r1 == 0 {
+		return err
+	}
+
+	r1, _, err = f.Call(windows.CTRL_C_EVENT, uintptr(pid))
+	if r1 == 0 {
+		return err
+	}
+
+	return nil
+}
+
+const STILL_ACTIVE = 259
+
+func isProcessExited(pid int) (bool, error) {
+	hProcess, err := windows.OpenProcess(windows.PROCESS_QUERY_INFORMATION, false, uint32(pid))
+	if err != nil {
+		return false, fmt.Errorf("failed to open process: %v", err)
+	}
+	defer windows.CloseHandle(hProcess) // nolint: errcheck
+
+	var exitCode uint32
+	err = windows.GetExitCodeProcess(hProcess, &exitCode)
+	if err != nil {
+		return false, fmt.Errorf("failed to get exit code: %v", err)
+	}
+
+	if exitCode == STILL_ACTIVE {
+		return false, nil
+	}
+
+	return true, nil
+}

app/lifecycle/updater.go

@@ -18,8 +18,8 @@ import (
 	"strings"
 	"time"
 
-	"github.com/jmorganca/ollama/auth"
-	"github.com/jmorganca/ollama/version"
+	"github.com/ollama/ollama/auth"
+	"github.com/ollama/ollama/version"
 )
 
 var (
@@ -34,20 +34,6 @@ type UpdateResponse struct {
 	UpdateVersion string `json:"version"`
 }
 
-func getClient(req *http.Request) http.Client {
-	proxyURL, err := http.ProxyFromEnvironment(req)
-	if err != nil {
-		slog.Warn(fmt.Sprintf("failed to handle proxy: %s", err))
-		return http.Client{}
-	}
-
-	return http.Client{
-		Transport: &http.Transport{
-			Proxy: http.ProxyURL(proxyURL),
-		},
-	}
-}
-
 func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
 	var updateResp UpdateResponse
 
@@ -83,10 +69,9 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
 	}
 	req.Header.Set("Authorization", signature)
 	req.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
-	client := getClient(req)
 
 	slog.Debug("checking for available update", "requestURL", requestURL)
-	resp, err := client.Do(req)
+	resp, err := http.DefaultClient.Do(req)
 	if err != nil {
 		slog.Warn(fmt.Sprintf("failed to check for update: %s", err))
 		return false, updateResp
@@ -101,6 +86,11 @@ func IsNewReleaseAvailable(ctx context.Context) (bool, UpdateResponse) {
 	if err != nil {
 		slog.Warn(fmt.Sprintf("failed to read body response: %s", err))
 	}
+
+	if resp.StatusCode != 200 {
+		slog.Info(fmt.Sprintf("check update error %d - %.96s", resp.StatusCode, string(body)))
+		return false, updateResp
+	}
 	err = json.Unmarshal(body, &updateResp)
 	if err != nil {
 		slog.Warn(fmt.Sprintf("malformed response checking for update: %s", err))
@@ -119,8 +109,8 @@ func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
 	if err != nil {
 		return err
 	}
-	client := getClient(req)
-	resp, err := client.Do(req)
+
+	resp, err := http.DefaultClient.Do(req)
 	if err != nil {
 		return fmt.Errorf("error checking update: %w", err)
 	}
@@ -151,7 +141,7 @@ func DownloadNewRelease(ctx context.Context, updateResp UpdateResponse) error {
 	cleanupOldDownloads()
 
 	req.Method = http.MethodGet
-	resp, err = client.Do(req)
+	resp, err = http.DefaultClient.Do(req)
 	if err != nil {
 		return fmt.Errorf("error checking update: %w", err)
 	}

app/main.go

@@ -4,7 +4,7 @@ package main
 // go build -ldflags="-H windowsgui" .
 
 import (
-	"github.com/jmorganca/ollama/app/lifecycle"
+	"github.com/ollama/ollama/app/lifecycle"
 )
 
 func main() {

app/ollama.iss

@@ -28,8 +28,8 @@ AppPublisher={#MyAppPublisher}
 AppPublisherURL={#MyAppURL}
 AppSupportURL={#MyAppURL}
 AppUpdatesURL={#MyAppURL}
-ArchitecturesAllowed=x64
-ArchitecturesInstallIn64BitMode=x64
+ArchitecturesAllowed=x64 arm64
+ArchitecturesInstallIn64BitMode=x64 arm64
 DefaultDirName={localappdata}\Programs\{#MyAppName}
 DefaultGroupName={#MyAppName}
 DisableProgramGroupPage=yes
@@ -49,9 +49,6 @@ SetupLogging=yes
 CloseApplications=yes
 RestartApplications=no
 
-; Make sure they can at least download llama2 as a minimum
-ExtraDiskSpaceRequired=3826806784
-
 ; https://jrsoftware.org/ishelp/index.php?topic=setup_wizardimagefile
 WizardSmallImageFile=.\assets\setup.bmp
 
@@ -91,9 +88,14 @@ DialogFontSize=12
 [Files]
 Source: ".\app.exe"; DestDir: "{app}"; DestName: "{#MyAppExeName}" ; Flags: ignoreversion 64bit
 Source: "..\ollama.exe"; DestDir: "{app}"; Flags: ignoreversion 64bit
-Source: "..\dist\windeps\*.dll"; 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"
@@ -116,7 +118,8 @@ Filename: "{cmd}"; Parameters: "/c timeout 5"; Flags: runhidden
 Type: filesandordirs; Name: "{%TEMP}\ollama*"
 Type: filesandordirs; Name: "{%LOCALAPPDATA}\Ollama"
 Type: filesandordirs; Name: "{%LOCALAPPDATA}\Programs\Ollama"
-Type: filesandordirs; Name: "{%USERPROFILE}\.ollama"
+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
 
 [Messages]
@@ -126,7 +129,7 @@ SetupAppRunningError=Another Ollama installer is running.%n%nPlease cancel or fi
 
 
 ;FinishedHeadingLabel=Run your first model
-;FinishedLabel=%nRun this command in a PowerShell or cmd terminal.%n%n%n    ollama run llama2
+;FinishedLabel=%nRun this command in a PowerShell or cmd terminal.%n%n%n    ollama run llama3
 ;ClickFinish=%n
 
 [Registry]

app/tray/tray.go

@@ -4,8 +4,8 @@ import (
 	"fmt"
 	"runtime"
 
-	"github.com/jmorganca/ollama/app/assets"
-	"github.com/jmorganca/ollama/app/tray/commontray"
+	"github.com/ollama/ollama/app/assets"
+	"github.com/ollama/ollama/app/tray/commontray"
 )
 
 func NewTray() (commontray.OllamaTray, error) {
@@ -24,10 +24,5 @@ func NewTray() (commontray.OllamaTray, error) {
 		return nil, fmt.Errorf("failed to load icon %s: %w", iconName, err)
 	}
 
-	tray, err := InitPlatformTray(icon, updateIcon)
-	if err != nil {
-		return nil, err
-	}
-
-	return tray, nil
+	return InitPlatformTray(icon, updateIcon)
 }

app/tray/tray_nonwindows.go

@@ -5,7 +5,7 @@ package tray
 import (
 	"fmt"
 
-	"github.com/jmorganca/ollama/app/tray/commontray"
+	"github.com/ollama/ollama/app/tray/commontray"
 )
 
 func InitPlatformTray(icon, updateIcon []byte) (commontray.OllamaTray, error) {

app/tray/tray_windows.go

@@ -1,8 +1,8 @@
 package tray
 
 import (
-	"github.com/jmorganca/ollama/app/tray/commontray"
-	"github.com/jmorganca/ollama/app/tray/wintray"
+	"github.com/ollama/ollama/app/tray/commontray"
+	"github.com/ollama/ollama/app/tray/wintray"
 )
 
 func InitPlatformTray(icon, updateIcon []byte) (commontray.OllamaTray, error) {

app/tray/wintray/tray.go

@@ -13,7 +13,7 @@ import (
 	"sync"
 	"unsafe"
 
-	"github.com/jmorganca/ollama/app/tray/commontray"
+	"github.com/ollama/ollama/app/tray/commontray"
 	"golang.org/x/sys/windows"
 )
 

cmd/cmd.go

@@ -1,6 +1,7 @@
 package cmd
 
 import (
+	"archive/zip"
 	"bytes"
 	"context"
 	"crypto/ed25519"
@@ -16,6 +17,7 @@ import (
 	"os"
 	"os/signal"
 	"path/filepath"
+	"regexp"
 	"runtime"
 	"strings"
 	"syscall"
@@ -29,12 +31,12 @@ import (
 	"golang.org/x/exp/slices"
 	"golang.org/x/term"
 
-	"github.com/jmorganca/ollama/api"
-	"github.com/jmorganca/ollama/format"
-	"github.com/jmorganca/ollama/parser"
-	"github.com/jmorganca/ollama/progress"
-	"github.com/jmorganca/ollama/server"
-	"github.com/jmorganca/ollama/version"
+	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/format"
+	"github.com/ollama/ollama/parser"
+	"github.com/ollama/ollama/progress"
+	"github.com/ollama/ollama/server"
+	"github.com/ollama/ollama/version"
 )
 
 func CreateHandler(cmd *cobra.Command, args []string) error {
@@ -52,8 +54,6 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
 	p := progress.NewProgress(os.Stderr)
 	defer p.Stop()
 
-	bars := make(map[string]*progress.Bar)
-
 	modelfile, err := os.ReadFile(filename)
 	if err != nil {
 		return err
@@ -87,29 +87,41 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
 				path = filepath.Join(filepath.Dir(filename), path)
 			}
 
-			bin, err := os.Open(path)
+			fi, err := os.Stat(path)
 			if errors.Is(err, os.ErrNotExist) && c.Name == "model" {
 				continue
 			} else if err != nil {
 				return err
 			}
-			defer bin.Close()
 
-			hash := sha256.New()
-			if _, err := io.Copy(hash, bin); err != nil {
-				return err
+			if fi.IsDir() {
+				// this is likely a safetensors or pytorch directory
+				// TODO make this work w/ adapters
+				tempfile, err := tempZipFiles(path)
+				if err != nil {
+					return err
+				}
+				defer os.RemoveAll(tempfile)
+
+				path = tempfile
 			}
-			bin.Seek(0, io.SeekStart)
 
-			digest := fmt.Sprintf("sha256:%x", hash.Sum(nil))
-			if err = client.CreateBlob(cmd.Context(), digest, bin); err != nil {
+			digest, err := createBlob(cmd, client, path)
+			if err != nil {
 				return err
 			}
 
-			modelfile = bytes.ReplaceAll(modelfile, []byte(c.Args), []byte("@"+digest))
+			name := c.Name
+			if c.Name == "model" {
+				name = "from"
+			}
+
+			re := regexp.MustCompile(fmt.Sprintf(`(?im)^(%s)\s+%s\s*$`, name, c.Args))
+			modelfile = re.ReplaceAll(modelfile, []byte("$1 @"+digest))
 		}
 	}
 
+	bars := make(map[string]*progress.Bar)
 	fn := func(resp api.ProgressResponse) error {
 		if resp.Digest != "" {
 			spinner.Stop()
@@ -133,7 +145,9 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
 		return nil
 	}
 
-	request := api.CreateRequest{Name: args[0], Modelfile: string(modelfile)}
+	quantization, _ := cmd.Flags().GetString("quantization")
+
+	request := api.CreateRequest{Name: args[0], Modelfile: string(modelfile), Quantization: quantization}
 	if err := client.Create(cmd.Context(), &request, fn); err != nil {
 		return err
 	}
@@ -141,6 +155,137 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
 	return nil
 }
 
+func tempZipFiles(path string) (string, error) {
+	tempfile, err := os.CreateTemp("", "ollama-tf")
+	if err != nil {
+		return "", err
+	}
+	defer tempfile.Close()
+
+	zipfile := zip.NewWriter(tempfile)
+	defer zipfile.Close()
+
+	detectContentType := func(path string) (string, error) {
+		f, err := os.Open(path)
+		if err != nil {
+			return "", err
+		}
+		defer f.Close()
+
+		var b bytes.Buffer
+		b.Grow(512)
+
+		if _, err := io.CopyN(&b, f, 512); err != nil && !errors.Is(err, io.EOF) {
+			return "", err
+		}
+
+		contentType, _, _ := strings.Cut(http.DetectContentType(b.Bytes()), ";")
+		return contentType, nil
+	}
+
+	glob := func(pattern, contentType string) ([]string, error) {
+		matches, err := filepath.Glob(pattern)
+		if err != nil {
+			return nil, err
+		}
+
+		for _, safetensor := range matches {
+			if ct, err := detectContentType(safetensor); err != nil {
+				return nil, err
+			} else if ct != contentType {
+				return nil, fmt.Errorf("invalid content type: expected %s for %s", ct, safetensor)
+			}
+		}
+
+		return matches, nil
+	}
+
+	var files []string
+	if st, _ := glob(filepath.Join(path, "model*.safetensors"), "application/octet-stream"); len(st) > 0 {
+		// safetensors files might be unresolved git lfs references; skip if they are
+		// covers model-x-of-y.safetensors, model.fp32-x-of-y.safetensors, model.safetensors
+		files = append(files, st...)
+	} else if pt, _ := glob(filepath.Join(path, "pytorch_model*.bin"), "application/zip"); len(pt) > 0 {
+		// pytorch files might also be unresolved git lfs references; skip if they are
+		// covers pytorch_model-x-of-y.bin, pytorch_model.fp32-x-of-y.bin, pytorch_model.bin
+		files = append(files, pt...)
+	} else if pt, _ := glob(filepath.Join(path, "consolidated*.pth"), "application/octet-stream"); len(pt) > 0 {
+		// pytorch files might also be unresolved git lfs references; skip if they are
+		// covers consolidated.x.pth, consolidated.pth
+		files = append(files, pt...)
+	} else {
+		return "", errors.New("no safetensors or torch files found")
+	}
+
+	// add configuration files, json files are detected as text/plain
+	js, err := glob(filepath.Join(path, "*.json"), "text/plain")
+	if err != nil {
+		return "", err
+	}
+	files = append(files, js...)
+
+	if tks, _ := glob(filepath.Join(path, "tokenizer.model"), "application/octet-stream"); len(tks) > 0 {
+		// add tokenizer.model if it exists, tokenizer.json is automatically picked up by the previous glob
+		// tokenizer.model might be a unresolved git lfs reference; error if it is
+		files = append(files, tks...)
+	} else if tks, _ := glob(filepath.Join(path, "**/tokenizer.model"), "text/plain"); len(tks) > 0 {
+		// some times tokenizer.model is in a subdirectory (e.g. meta-llama/Meta-Llama-3-8B)
+		files = append(files, tks...)
+	}
+
+	for _, file := range files {
+		f, err := os.Open(file)
+		if err != nil {
+			return "", err
+		}
+		defer f.Close()
+
+		fi, err := f.Stat()
+		if err != nil {
+			return "", err
+		}
+
+		zfi, err := zip.FileInfoHeader(fi)
+		if err != nil {
+			return "", err
+		}
+
+		zf, err := zipfile.CreateHeader(zfi)
+		if err != nil {
+			return "", err
+		}
+
+		if _, err := io.Copy(zf, f); err != nil {
+			return "", err
+		}
+	}
+
+	return tempfile.Name(), nil
+}
+
+func createBlob(cmd *cobra.Command, client *api.Client, path string) (string, error) {
+	bin, err := os.Open(path)
+	if err != nil {
+		return "", err
+	}
+	defer bin.Close()
+
+	hash := sha256.New()
+	if _, err := io.Copy(hash, bin); err != nil {
+		return "", err
+	}
+
+	if _, err := bin.Seek(0, io.SeekStart); err != nil {
+		return "", err
+	}
+
+	digest := fmt.Sprintf("sha256:%x", hash.Sum(nil))
+	if err = client.CreateBlob(cmd.Context(), digest, bin); err != nil {
+		return "", err
+	}
+	return digest, nil
+}
+
 func RunHandler(cmd *cobra.Command, args []string) error {
 	client, err := api.ClientFromEnvironment()
 	if err != nil {
@@ -718,39 +863,36 @@ func initializeKeypair() error {
 	_, err = os.Stat(privKeyPath)
 	if os.IsNotExist(err) {
 		fmt.Printf("Couldn't find '%s'. Generating new private key.\n", privKeyPath)
-		_, privKey, err := ed25519.GenerateKey(rand.Reader)
+		cryptoPublicKey, cryptoPrivateKey, err := ed25519.GenerateKey(rand.Reader)
 		if err != nil {
 			return err
 		}
 
-		privKeyBytes, err := format.OpenSSHPrivateKey(privKey, "")
+		privateKeyBytes, err := ssh.MarshalPrivateKey(cryptoPrivateKey, "")
 		if err != nil {
 			return err
 		}
 
-		err = os.MkdirAll(filepath.Dir(privKeyPath), 0o755)
-		if err != nil {
+		if err := os.MkdirAll(filepath.Dir(privKeyPath), 0o755); err != nil {
 			return fmt.Errorf("could not create directory %w", err)
 		}
 
-		err = os.WriteFile(privKeyPath, pem.EncodeToMemory(privKeyBytes), 0o600)
+		if err := os.WriteFile(privKeyPath, pem.EncodeToMemory(privateKeyBytes), 0o600); err != nil {
+			return err
+		}
+
+		sshPublicKey, err := ssh.NewPublicKey(cryptoPublicKey)
 		if err != nil {
 			return err
 		}
 
-		sshPrivateKey, err := ssh.NewSignerFromKey(privKey)
-		if err != nil {
+		publicKeyBytes := ssh.MarshalAuthorizedKey(sshPublicKey)
+
+		if err := os.WriteFile(pubKeyPath, publicKeyBytes, 0o644); err != nil {
 			return err
 		}
 
-		pubKeyData := ssh.MarshalAuthorizedKey(sshPrivateKey.PublicKey())
-
-		err = os.WriteFile(pubKeyPath, pubKeyData, 0o644)
-		if err != nil {
-			return err
-		}
-
-		fmt.Printf("Your new public key is: \n\n%s\n", string(pubKeyData))
+		fmt.Printf("Your new public key is: \n\n%s\n", publicKeyBytes)
 	}
 	return nil
 }
@@ -809,13 +951,20 @@ func versionHandler(cmd *cobra.Command, _ []string) {
 	}
 }
 
+func appendHostEnvDocs(cmd *cobra.Command) {
+	const hostEnvDocs = `
+Environment Variables:
+      OLLAMA_HOST        The host:port or base URL of the Ollama server (e.g. http://localhost:11434)
+`
+	cmd.SetUsageTemplate(cmd.UsageTemplate() + hostEnvDocs)
+}
+
 func NewCLI() *cobra.Command {
 	log.SetFlags(log.LstdFlags | log.Lshortfile)
 	cobra.EnableCommandSorting = false
 
 	if runtime.GOOS == "windows" {
-		// Enable colorful ANSI escape code in Windows terminal (disabled by default)
-		console.ConsoleFromFile(os.Stdout) //nolint:errcheck
+		console.ConsoleFromFile(os.Stdin) //nolint:errcheck
 	}
 
 	rootCmd := &cobra.Command{
@@ -847,6 +996,7 @@ func NewCLI() *cobra.Command {
 	}
 
 	createCmd.Flags().StringP("file", "f", "Modelfile", "Name of the Modelfile (default \"Modelfile\")")
+	createCmd.Flags().StringP("quantization", "q", "", "Quantization level.")
 
 	showCmd := &cobra.Command{
 		Use:     "show MODEL",
@@ -874,7 +1024,6 @@ func NewCLI() *cobra.Command {
 	runCmd.Flags().Bool("insecure", false, "Use an insecure registry")
 	runCmd.Flags().Bool("nowordwrap", false, "Don't wrap words to the next line automatically")
 	runCmd.Flags().String("format", "", "Response format (e.g. json)")
-
 	serveCmd := &cobra.Command{
 		Use:     "serve",
 		Aliases: []string{"start"},
@@ -882,6 +1031,15 @@ func NewCLI() *cobra.Command {
 		Args:    cobra.ExactArgs(0),
 		RunE:    RunServer,
 	}
+	serveCmd.SetUsageTemplate(serveCmd.UsageTemplate() + `
+Environment Variables:
+
+    OLLAMA_HOST         The host:port to bind to (default "127.0.0.1:11434")
+    OLLAMA_ORIGINS      A comma separated list of allowed origins.
+    OLLAMA_MODELS       The path to the models directory (default is "~/.ollama/models")
+    OLLAMA_KEEP_ALIVE   The duration that models stay loaded in memory (default is "5m")
+    OLLAMA_DEBUG        Set to 1 to enable additional debug logging
+`)
 
 	pullCmd := &cobra.Command{
 		Use:     "pull MODEL",
@@ -910,7 +1068,6 @@ func NewCLI() *cobra.Command {
 		PreRunE: checkServerHeartbeat,
 		RunE:    ListHandler,
 	}
-
 	copyCmd := &cobra.Command{
 		Use:     "cp SOURCE TARGET",
 		Short:   "Copy a model",
@@ -927,6 +1084,19 @@ func NewCLI() *cobra.Command {
 		RunE:    DeleteHandler,
 	}
 
+	for _, cmd := range []*cobra.Command{
+		createCmd,
+		showCmd,
+		runCmd,
+		pullCmd,
+		pushCmd,
+		listCmd,
+		copyCmd,
+		deleteCmd,
+	} {
+		appendHostEnvDocs(cmd)
+	}
+
 	rootCmd.AddCommand(
 		serveCmd,
 		createCmd,

cmd/interactive.go

@@ -14,9 +14,9 @@ import (
 	"github.com/spf13/cobra"
 	"golang.org/x/exp/slices"
 
-	"github.com/jmorganca/ollama/api"
-	"github.com/jmorganca/ollama/progress"
-	"github.com/jmorganca/ollama/readline"
+	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/progress"
+	"github.com/ollama/ollama/readline"
 )
 
 type MultilineState int
@@ -295,10 +295,14 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 					opts.WordWrap = false
 					fmt.Println("Set 'nowordwrap' mode.")
 				case "verbose":
-					cmd.Flags().Set("verbose", "true")
+					if err := cmd.Flags().Set("verbose", "true"); err != nil {
+						return err
+					}
 					fmt.Println("Set 'verbose' mode.")
 				case "quiet":
-					cmd.Flags().Set("verbose", "false")
+					if err := cmd.Flags().Set("verbose", "false"); err != nil {
+						return err
+					}
 					fmt.Println("Set 'quiet' mode.")
 				case "format":
 					if len(args) < 3 || args[2] != "json" {

cmd/interactive_test.go

@@ -7,7 +7,7 @@ import (
 
 	"github.com/stretchr/testify/assert"
 
-	"github.com/jmorganca/ollama/api"
+	"github.com/ollama/ollama/api"
 )
 
 func TestExtractFilenames(t *testing.T) {

cmd/start_darwin.go

@@ -7,7 +7,7 @@ import (
 	"os/exec"
 	"strings"
 
-	"github.com/jmorganca/ollama/api"
+	"github.com/ollama/ollama/api"
 )
 
 func startApp(ctx context.Context, client *api.Client) error {

cmd/start_default.go

@@ -6,7 +6,7 @@ import (
 	"context"
 	"fmt"
 
-	"github.com/jmorganca/ollama/api"
+	"github.com/ollama/ollama/api"
 )
 
 func startApp(ctx context.Context, client *api.Client) error {

cmd/start_windows.go

@@ -10,7 +10,7 @@ import (
 	"strings"
 	"syscall"
 
-	"github.com/jmorganca/ollama/api"
+	"github.com/ollama/ollama/api"
 )
 
 func startApp(ctx context.Context, client *api.Client) error {

convert/convert.go

@@ -0,0 +1,187 @@
+package convert
+
+import (
+	"cmp"
+	"encoding/binary"
+	"encoding/json"
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"slices"
+	"strings"
+
+	"google.golang.org/protobuf/proto"
+
+	"github.com/ollama/ollama/convert/sentencepiece"
+	"github.com/ollama/ollama/llm"
+)
+
+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 ByteOrder interface {
+	binary.ByteOrder
+	binary.AppendByteOrder
+}
+
+type ModelArch interface {
+	GetTensors() error
+	LoadVocab() error
+	WriteGGUF() (string, error)
+}
+
+type ModelFormat interface {
+	GetLayerName(string) (string, error)
+	GetTensors(string, *Params) ([]llm.Tensor, error)
+	GetParams(string) (*Params, error)
+	GetModelArch(string, string, *Params) (ModelArch, error)
+}
+
+type ModelData struct {
+	Path    string
+	Name    string
+	Params  *Params
+	Vocab   *Vocab
+	Tensors []llm.Tensor
+	Format  ModelFormat
+}
+
+func GetModelFormat(dirname string) (ModelFormat, error) {
+	files, err := filepath.Glob(filepath.Join(dirname, "*"))
+	if err != nil {
+		return nil, 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
+		}
+	}
+
+	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
+}

convert/gemma.go

@@ -0,0 +1,137 @@
+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
+}

convert/llama.go

@@ -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
+}

convert/mistral.go

@@ -0,0 +1,173 @@
+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
+}

convert/mixtral.go

@@ -0,0 +1,96 @@
+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
+}

convert/safetensors.go

@@ -0,0 +1,317 @@
+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")
+}

convert/sentencepiece_model.proto

@@ -0,0 +1,333 @@
+// Copyright 2016 Google Inc.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.!
+
+syntax = "proto2";
+
+// TODO(taku): Needs to use LITE RUNTIME in OSS release.
+option optimize_for = LITE_RUNTIME;
+option go_package = "./sentencepiece";
+
+package sentencepiece;
+
+// TrainerSpec encodes a various parameters for SentencePiece training.
+// Next id: 55
+message TrainerSpec {
+  ///////////////////////////////////////////////////////////////////
+  // General parameters
+  //
+  // Input corpus files.
+  //  Trainer accepts the following two formats:
+  //  A) Monolingual: plain text, one sentence per line.
+  //  B) Bilingual:   TSV, source sentence <tab> target sentence
+  //  When bilingual data is passed, shared vocabulary model is built.
+  //  Note that the input file must be raw corpus, not a preprocessed corpus.
+  //  Trainer only loads the first `input_sentence_size` sentences specified
+  //  with this parameter.
+  repeated string input = 1;
+
+  // Input corpus format:
+  // "text": one-sentence-per-line text format (default)
+  // "tsv":  sentence <tab> freq
+  optional string input_format = 7;
+
+  // Output model file prefix.
+  // <model_prefix>.model and <model_prefix>.vocab are generated.
+  optional string model_prefix = 2;
+
+  // Model type. only have UNIGRAM now.
+  enum ModelType {
+    UNIGRAM = 1;  // Unigram language model with dynamic algorithm
+    BPE = 2;      // Byte Pair Encoding
+    WORD = 3;     // Delimitered by whitespace.
+    CHAR = 4;     // tokenizes into character sequence
+  }
+  optional ModelType model_type = 3 [default = UNIGRAM];
+
+  // Vocabulary size. 8k is the default size.
+  optional int32 vocab_size = 4 [default = 8000];
+
+  // List of the languages this model can accept.
+  // Since the model is language-agnostic, this field is used as a reference.
+  repeated string accept_language = 5;
+
+  // Size of self-test samples, which are encoded in the model file.
+  optional int32 self_test_sample_size = 6 [default = 0];
+
+  // Whether to use DP version of sentencepiece. Use it with TSV input format
+  // (requires precomputed word tab counts to work).
+  optional bool enable_differential_privacy = 50 [default = false];
+  // Set these parameters if you need DP version of sentencepiece.
+  // std of noise to add.
+  optional float differential_privacy_noise_level = 51 [default = 0.0];
+  // Clipping threshold to apply after adding noise. All the words with
+  // frequency less than this value are dropped.
+  optional uint64 differential_privacy_clipping_threshold = 52 [default = 0];
+
+  ///////////////////////////////////////////////////////////////////
+  // Training parameters.
+  //
+  // Uses characters which cover the corpus with the ratio of `chars_coverage`.
+  // This parameter determines the set of basic Alphabet of sentence piece.
+  // 1.0 - `chars_coverage` characters are treated as UNK.
+  // See also required_chars field.
+  optional float character_coverage = 10 [default = 0.9995];
+
+  // Maximum size of sentences the trainer loads from `input` parameter.
+  // Trainer simply loads the `input` files in sequence.
+  // It is better to shuffle the input corpus randomly.
+  optional uint64 input_sentence_size = 11 [default = 0];
+  optional bool shuffle_input_sentence = 19 [default = true];
+
+  // Maximum size of sentences to make seed sentence pieces.
+  // Extended suffix array is constructed to extract frequent
+  // sub-strings from the corpus. This uses 20N working space,
+  // where N is the size of corpus.
+  optional int32 mining_sentence_size = 12 [deprecated = true];
+
+  // Maximum size of sentences to train sentence pieces.
+  optional int32 training_sentence_size = 13 [deprecated = true];
+
+  // The size of seed sentencepieces.
+  // `seed_sentencepiece_size` must be larger than `vocab_size`.
+  optional int32 seed_sentencepiece_size = 14 [default = 1000000];
+
+  // In every EM sub-iterations, keeps top
+  // `shrinking_factor` * `current sentencepieces size` with respect to
+  // the loss of the sentence piece. This value should be smaller than 1.0.
+  optional float shrinking_factor = 15 [default = 0.75];
+
+  // The maximum sentence length in byte. The sentences with the length
+  // larger than `max_sentence_length` is simply ignored.
+  // Longer input tends to bring the following risks:
+  //  * Overflow during EM training (unigram language model only)
+  //  * Performance drop because of O(n log n) cost in BPE.
+  optional int32 max_sentence_length = 18 [default = 4192];
+
+  // Number of threads in the training.
+  optional int32 num_threads = 16 [default = 16];
+
+  // Number of EM sub iterations.
+  optional int32 num_sub_iterations = 17 [default = 2];
+
+  ///////////////////////////////////////////////////////////////////
+  // SentencePiece parameters which control the shapes of sentence piece.
+  //
+  // Maximum length of sentencepiece.
+  optional int32 max_sentencepiece_length = 20 [default = 16];
+
+  // Uses Unicode script to split sentence pieces.
+  // When `split_by_unicode_script` is true, we do not allow sentence piece to
+  // include multiple Unicode scripts, e.g. "F1" is not a valid piece.
+  // Exception: CJ characters (Hiragana/Katakana/Han) are all handled
+  // as one script type, since Japanese word can consist of multiple scripts.
+  // This exception is always applied regardless of the accept-language
+  // parameter.
+  optional bool split_by_unicode_script = 21 [default = true];
+
+  // When `split_by_number` is true, put a boundary between number and
+  // non-number transition. If we want to treat "F1" is one token, set this flag
+  // to be false.
+  optional bool split_by_number = 23 [default = true];
+
+  // Use a white space to split sentence pieces.
+  // When `split_by_whitespace` is false, we may have the piece containing
+  // a white space in the middle. e.g., "in_the".
+  optional bool split_by_whitespace = 22 [default = true];
+
+  // Adds whitespace symbol (_) as a suffix instead of prefix. e.g., _hello =>
+  // hello_. When `treat_whitespace_as_suffix` is true,
+  // NormalizerSpec::add_dummy_prefix will add the dummy whitespace to the end
+  // of sentence.
+  optional bool treat_whitespace_as_suffix = 24 [default = false];
+
+  // Allows pieces that only contain whitespaces instead of appearing only as
+  // prefix or suffix of other pieces.
+  optional bool allow_whitespace_only_pieces = 26 [default = false];
+
+  // Split all digits (0-9) into separate pieces.
+  optional bool split_digits = 25 [default = false];
+
+  // Defines the pre-tokenization delimiter.
+  // When specified, no pieces crossing this delimiter is not included
+  // in the vocab. Then the delimiter string is virtually ignored
+  // during the training. This field can allows constraints on the vocabulary
+  // selection. Note that this field is available on unigram mode.
+  optional string pretokenization_delimiter = 53 [ default = ""];
+
+  ///////////////////////////////////////////////////////////////////
+  // Vocabulary management
+  //
+  // Defines control symbols used as an indicator to
+  // change the behavior of the decoder. <s> and </s> are pre-defined.
+  // We can use this field to encode various meta information,
+  // including language indicator in multilingual model.
+  // These symbols are not visible to users, but visible to
+  // the decoder. Note that when the input sentence contains control symbols,
+  // they are not treated as one token, but segmented into normal pieces.
+  // Control symbols must be inserted independently from the segmentation.
+  repeated string control_symbols = 30;
+
+  // Defines user defined symbols.
+  // These symbols are added with extremely high score
+  // so they are always treated as one unique symbol in any context.
+  // Typical usage of user_defined_symbols is placeholder for named entities.
+  repeated string user_defined_symbols = 31;
+
+  // Defines required characters. Each UTF8 character in this string is included
+  // in the character set regardless of character_coverage value. Unlike
+  // user_defined_symbols, these characters have scores based on the frequency
+  // on input sentences, and the model can form subwords using characters
+  // in this field.
+  optional string required_chars = 36;
+
+  // Decomposes unknown pieces into UTF-8 bytes.
+  optional bool byte_fallback = 35 [default = false];
+
+  // When creating the vocabulary file, defines whether or not to additionally
+  // output the score for each piece.
+  optional bool vocabulary_output_piece_score = 32 [default = true];
+
+  // `vocab_size` is treated as hard limit. Crash if
+  // the model can not produce the vocab of size `vocab_size`,
+  // When `hard_vocab_limit` is false, vocab_size is treated
+  // as soft limit. Note that when model_type=char,
+  // always assumes hard_vocab_limit = false.
+  optional bool hard_vocab_limit = 33 [default = true];
+
+  // use all symbols for vocab extraction. This flag is valid
+  // if model type is either CHAR or WORD
+  optional bool use_all_vocab = 34 [default = false];
+
+  ///////////////////////////////////////////////////////////////////
+  // Reserved special meta tokens.
+  // * -1 is not used.
+  // * unk_id must not be -1.
+  // Id must starts with 0 and be contigous.
+  optional int32 unk_id = 40 [default = 0];   // <unk>
+  optional int32 bos_id = 41 [default = 1];   // <s>
+  optional int32 eos_id = 42 [default = 2];   // </s>
+  optional int32 pad_id = 43 [default = -1];  // <pad> (padding)
+  optional string unk_piece = 45 [default = "<unk>"];
+  optional string bos_piece = 46 [default = "<s>"];
+  optional string eos_piece = 47 [default = "</s>"];
+  optional string pad_piece = 48 [default = "<pad>"];
+
+  // Encodes <unk> into U+2047 (DOUBLE QUESTION MARK),
+  // since this character can be useful both for user and
+  // developer. We can easily figure out that <unk> is emitted.
+  optional string unk_surface = 44 [default = " \xE2\x81\x87 "];
+
+  // Increase bit depth to allow unigram model training on large
+  // (>10M sentences) corpora. A Side-effect of enabling this flag
+  // is increased memory usage.
+  optional bool train_extremely_large_corpus = 49 [default = false];
+
+ // Path to a seed sentencepieces file, with one tab-separated
+  // seed sentencepiece <tab> frequency per line.
+  optional string seed_sentencepieces_file = 54 [default = ""];
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}
+
+// NormalizerSpec encodes a various parameters for string normalizaiton
+message NormalizerSpec {
+  // name of normalization rule.
+  optional string name = 1;
+
+  // Pre-compiled normalization rule created by
+  // Builder::GetPrecompiledCharsMap() or Builder::CompileCharsMap() method.
+  // Usually this field is set by Builder::GetNormalizerSpec() method.
+  optional bytes precompiled_charsmap = 2;
+
+  // Adds dummy whitespace at the beginning of text in order to
+  // treat "world" in "world" and "hello world" in the same way.
+  optional bool add_dummy_prefix = 3 [default = true];
+
+  // Removes leading, trailing, and duplicate internal whitespace.
+  optional bool remove_extra_whitespaces = 4 [default = true];
+
+  // Replaces whitespace with meta symbol.
+  // This field must be true to train sentence piece model.
+  optional bool escape_whitespaces = 5 [default = true];
+
+  // Custom normalization rule file in TSV format.
+  // https://github.com/google/sentencepiece/blob/master/doc/normalization.md
+  // This field is only used in SentencePieceTrainer::Train() method, which
+  // compiles the rule into the binary rule stored in `precompiled_charsmap`.
+  optional string normalization_rule_tsv = 6;
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}
+
+// Proto to store samples for self-testing.
+message SelfTestData {
+  message Sample {
+    optional string input = 1;
+    optional string expected = 2;
+  }
+  repeated Sample samples = 1;
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}
+
+// ModelProto stores model parameters.
+// SentencePieceProcessor is supposed to be self-contained.
+// All settings/parameters which may change the behavior must be encoded
+// in ModelProto.
+message ModelProto {
+  message SentencePiece {
+    enum Type {
+      NORMAL = 1;        // normal symbol
+      UNKNOWN = 2;       // unknown symbol. only <unk> for now.
+      CONTROL = 3;       // control symbols. </s>, <s>, <2ja> etc.
+      USER_DEFINED = 4;  // user defined symbols.
+                         // Typical usage of USER_DEFINED symbol
+                         // is placeholder.
+      BYTE = 6;          // byte symbols. Used when `byte_fallback` is true.
+      UNUSED = 5;        // this piece is not used.
+    }
+    optional string piece = 1;  // piece must not be empty.
+    optional float score = 2;
+    optional Type type = 3 [default = NORMAL];
+
+    // Customized extensions: the range of field numbers
+    // are open to third-party extensions.
+    extensions 200 to max;
+  }
+
+  // Sentence pieces with scores.
+  repeated SentencePiece pieces = 1;
+
+  // Spec used to generate this model file.
+  optional TrainerSpec trainer_spec = 2;
+
+  // Spec for text normalization.
+  optional NormalizerSpec normalizer_spec = 3;
+
+  // Stores sample input and its expected segmentation to verify the model.
+  optional SelfTestData self_test_data = 4;
+
+  // Spec for text de-normalization.
+  optional NormalizerSpec denormalizer_spec = 5;
+
+  // Customized extensions: the range of field numbers
+  // are open to third-party extensions.
+  extensions 200 to max;
+}

convert/torch.go

@@ -0,0 +1,286 @@
+package convert
+
+import (
+	"encoding/binary"
+	"encoding/json"
+	"fmt"
+	"io"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"regexp"
+	"strings"
+
+	"github.com/nlpodyssey/gopickle/pytorch"
+	"github.com/nlpodyssey/gopickle/types"
+	"github.com/x448/float16"
+
+	"github.com/ollama/ollama/llm"
+)
+
+type torchWriterTo struct {
+	t *llm.Tensor
+
+	params *Params
+	bo     ByteOrder
+
+	storage pytorch.StorageInterface
+	handler func(w io.Writer, r torchWriterTo) error
+}
+
+type TorchFormat struct{}
+
+func (tf *TorchFormat) GetTensors(dirpath string, params *Params) ([]llm.Tensor, error) {
+	slog.Debug("getting torch tensors")
+
+	files, err := filepath.Glob(filepath.Join(dirpath, "pytorch_model-*.bin"))
+	if err != nil {
+		slog.Error("didn't find any torch files")
+		return nil, err
+	}
+
+	var offset uint64
+
+	var tensors []llm.Tensor
+	for _, fn := range files {
+		m, err := pytorch.Load(fn)
+		if err != nil {
+			slog.Error(fmt.Sprintf("error unpickling: %q", err))
+			return []llm.Tensor{}, err
+		}
+
+		for _, k := range m.(*types.Dict).Keys() {
+			if strings.HasSuffix(k.(string), "self_attn.rotary_emb.inv_freq") {
+				continue
+			}
+
+			t, _ := m.(*types.Dict).Get(k)
+			tshape := t.(*pytorch.Tensor).Size
+
+			var size uint64
+			var kind uint32
+			switch len(tshape) {
+			case 0:
+				continue
+			case 1:
+				// convert to float32
+				kind = 0
+				size = uint64(tshape[0] * 4)
+			case 2:
+				// convert to float16
+				kind = 1
+				size = uint64(tshape[0] * tshape[1] * 2)
+			}
+
+			ggufName, err := tf.GetLayerName(k.(string))
+			if err != nil {
+				slog.Error("%v", err)
+				return nil, err
+			}
+			slog.Debug(fmt.Sprintf("finding name for '%s' -> '%s'", k.(string), ggufName))
+
+			shape := []uint64{0, 0, 0, 0}
+			for i := range tshape {
+				shape[i] = uint64(tshape[i])
+			}
+
+			tensor := llm.Tensor{
+				Name:   ggufName,
+				Kind:   kind,
+				Offset: offset, // calculate the offset
+				Shape:  shape[:],
+			}
+
+			tensor.WriterTo = torchWriterTo{
+				t:       &tensor,
+				params:  params,
+				bo:      params.ByteOrder,
+				storage: t.(*pytorch.Tensor).Source,
+			}
+
+			tensors = append(tensors, tensor)
+			offset += size
+		}
+	}
+
+	return tensors, nil
+
+}
+
+func getAltParams(dirpath string) (*Params, error) {
+	f, err := os.Open(filepath.Join(dirpath, "params.json"))
+	if err != nil {
+		slog.Error("no params.json")
+		return nil, err
+	}
+	defer f.Close()
+
+	type TorchParams struct {
+		HiddenSize     int     `json:"dim"`
+		AttentionHeads int     `json:"n_heads"`
+		KeyValHeads    int     `json:"n_kv_heads"`
+		HiddenLayers   int     `json:"n_layers"`
+		RopeTheta      int     `json:"rope_theta"`
+		NormEPS        float64 `json:"norm_eps"`
+	}
+
+	var tparams TorchParams
+
+	d := json.NewDecoder(f)
+	err = d.Decode(&tparams)
+	if err != nil {
+		return nil, err
+	}
+
+	params := &Params{
+		HiddenSize:     tparams.HiddenSize,
+		AttentionHeads: tparams.AttentionHeads,
+		KeyValHeads:    tparams.KeyValHeads,
+		HiddenLayers:   tparams.HiddenLayers,
+		NormEPS:        tparams.NormEPS,
+	}
+
+	switch {
+	case tparams.RopeTheta == 1000000:
+		// Codellama
+		params.ContextSize = 16384
+	case tparams.NormEPS == 1e-06:
+		// llama2
+		slog.Debug("Found llama2 - setting context size to 4096")
+		params.ContextSize = 4096
+	default:
+		params.ContextSize = 2048
+	}
+
+	params.ByteOrder = binary.LittleEndian
+	return params, nil
+}
+
+func (m *TorchFormat) GetParams(dirpath string) (*Params, error) {
+	f, err := os.Open(filepath.Join(dirpath, "config.json"))
+	if err != nil {
+		if os.IsNotExist(err) {
+			// try params.json instead
+			return getAltParams(dirpath)
+		} else {
+			return nil, err
+		}
+	}
+
+	var params Params
+	d := json.NewDecoder(f)
+	err = d.Decode(&params)
+	if err != nil {
+		return nil, err
+	}
+
+	params.ByteOrder = binary.LittleEndian
+	return &params, nil
+}
+
+func (m *TorchFormat) GetLayerName(n string) (string, error) {
+	directMap := map[string]string{
+		"tok_embeddings.weight":     "token_embd.weight",
+		"output.weight":             "output.weight",
+		"norm.weight":               "output_norm.weight",
+		"rope.freqs":                "rope_freqs.weight",
+		"model.embed_tokens.weight": "token_embd.weight",
+		"lm_head.weight":            "output.weight",
+		"model.norm.weight":         "output_norm.weight",
+	}
+
+	lMap := map[string]string{
+		"layers.(\\d+).attention_norm.weight":                 "blk.$1.attn_norm.weight",
+		"layers.(\\d+).attention_output_norm.weight":          "blk.$1.attn_norm.weight",
+		"layers.(\\d+).feed_forward.w2.weight":                "blk.$1.ffn_down.weight",
+		"layers.(\\d+).feed_forward.w1.weight":                "blk.$1.ffn_gate.weight",
+		"layers.(\\d+).feed_forward.w3.weight":                "blk.$1.ffn_up.weight",
+		"layers.(\\d+).ffn_norm.weight":                       "blk.$1.ffn_norm.weight",
+		"layers.(\\d+).attention.wk.weight":                   "blk.$1.attn_k.weight",
+		"layers.(\\d+).attention.wo.weight":                   "blk.$1.attn_output.weight",
+		"layers.(\\d+).attention.wq.weight":                   "blk.$1.attn_q.weight",
+		"layers.(\\d+).attention.wv.weight":                   "blk.$1.attn_v.weight",
+		"model.layers.(\\d+).input_layernorm.weight":          "blk.$1.attn_norm.weight",
+		"model.layers.(\\d+).mlp.down_proj.weight":            "blk.$1.ffn_down.weight",
+		"model.layers.(\\d+).mlp.gate_proj.weight":            "blk.$1.ffn_gate.weight",
+		"model.layers.(\\d+).mlp.up_proj.weight":              "blk.$1.ffn_up.weight",
+		"model.layers.(\\d+).post_attention_layernorm.weight": "blk.$1.ffn_norm.weight",
+		"model.layers.(\\d+).self_attn.k_proj.weight":         "blk.$1.attn_k.weight",
+		"model.layers.(\\d+).self_attn.o_proj.weight":         "blk.$1.attn_output.weight",
+		"model.layers.(\\d+).self_attn.q_proj.weight":         "blk.$1.attn_q.weight",
+		"model.layers.(\\d+).self_attn.v_proj.weight":         "blk.$1.attn_v.weight",
+	}
+
+	v, ok := directMap[n]
+	if ok {
+		return v, nil
+	}
+
+	// quick hack to rename the layers to gguf format
+	for k, v := range lMap {
+		re := regexp.MustCompile(k)
+		newName := re.ReplaceAllString(n, v)
+		if newName != n {
+			return newName, nil
+		}
+	}
+
+	return "", fmt.Errorf("couldn't find a layer name for '%s'", n)
+}
+
+func (r torchWriterTo) WriteTo(w io.Writer) (n int64, err error) {
+	// use the handler if one is present
+	if r.handler != nil {
+		return 0, r.handler(w, r)
+	}
+
+	switch r.storage.(type) {
+	case *pytorch.FloatStorage:
+		slog.Warn(fmt.Sprintf("unexpected storage found for layer '%s'; skipping", r.t.Name))
+		return 0, nil
+	case *pytorch.HalfStorage:
+		switch r.t.Kind {
+		case 0:
+			data := r.storage.(*pytorch.HalfStorage).Data
+			slog.Debug(fmt.Sprintf("%35s F32 (%d)", r.t.Name, len(data)))
+			if err := binary.Write(w, r.bo, data); err != nil {
+				return 0, err
+			}
+		case 1:
+			data := r.storage.(*pytorch.HalfStorage).Data
+			tData := make([]uint16, len(data))
+			for cnt, v := range data {
+				tData[cnt] = uint16(float16.Fromfloat32(v))
+			}
+			slog.Debug(fmt.Sprintf("%35s F16 (%d)", r.t.Name, len(tData)))
+			if err := binary.Write(w, r.bo, tData); err != nil {
+				return 0, err
+			}
+		}
+	}
+
+	return 0, nil
+}
+
+func (m *TorchFormat) GetModelArch(name, dirPath string, params *Params) (ModelArch, error) {
+	switch len(params.Architectures) {
+	case 0:
+		return nil, fmt.Errorf("No architecture specified to convert")
+	case 1:
+		switch params.Architectures[0] {
+		case "LlamaForCausalLM":
+			return &LlamaModel{
+				ModelData{
+					Name:   name,
+					Path:   dirPath,
+					Params: params,
+					Format: m,
+				},
+			}, nil
+		default:
+			return nil, fmt.Errorf("Models based on '%s' are not yet supported", params.Architectures[0])
+		}
+	}
+
+	return nil, fmt.Errorf("Unknown error")
+}

docs/README.md

@@ -1,25 +1,21 @@
 # Documentation
 
-To get started, see the project's **[quickstart](../README.md#quickstart)**.
+### Getting Started
+* [Quickstart](../README.md#quickstart)
+* [Examples](../examples)
+* [Importing models](./import.md)
+* [Linux Documentation](./linux.md)
+* [Windows Documentation](./windows.md)
+* [Docker Documentation](https://hub.docker.com/r/ollama/ollama)
 
-Ollama is a tool for running AI models on your hardware. Many users will choose to use the Command Line Interface (CLI) to work with Ollama. Learn more about all the commands in the CLI in the **[Main Readme](../README.md)**.
+### Reference
 
-Use the RESTful API using any language, including Python, JavaScript, Typescript, Go, Rust, and many more. Learn more about using the API in the **[API Documentation](./api.md)**.
+* [API Reference](./api.md)
+* [Modelfile Reference](./modelfile.md)
+* [OpenAI Compatibility](./openai.md)
 
-Create new models or modify models already in the library using the Modelfile. Learn more about the Modelfile syntax in the **[Modelfile Documentation](./modelfile.md)**.
+### Resources
 
-Import models using source model weights found on Hugging Face and similar sites by referring to the **[Import Documentation](./import.md)**.
-
-Installing on Linux in most cases is easy using the script on [ollama.com/download](ollama.com/download). To get more detail about the install, including CUDA drivers, see the **[Linux Documentation](./linux.md)**.
-
-Many of our users like the flexibility of using our official Docker Image. Learn more about using Docker with Ollama using the **[Docker Documentation](https://hub.docker.com/r/ollama/ollama)**.
-
-It is easy to install on Linux and Mac, but many users will choose to build Ollama on their own. To do this, refer to the **[Development Documentation](./development.md)**.
-
-If encountering a problem with Ollama, the best place to start is the logs. Find more information about them here in the **[Troubleshooting Guide](./troubleshooting.md)**.
-
-Finally for all the questions that don't fit anywhere else, there is the **[FAQ](./faq.md)**
-
-[Tutorials](./tutorials.md) apply the documentation to tasks.
-
-For working code examples of using Ollama, see [Examples](../examples).
+* [Troubleshooting Guide](./troubleshooting.md)
+* [FAQ](./faq.md)
+* [Development guide](./development.md)

docs/api.md

@@ -54,7 +54,7 @@ Advanced parameters (optional):
 
 #### JSON mode
 
-Enable JSON mode by setting the `format` parameter to `json`. This will structure the response as a valid JSON object. See the JSON mode [example](#generate-request-json-mode) below.
+Enable JSON mode by setting the `format` parameter to `json`. This will structure the response as a valid JSON object. See the JSON mode [example](#request-json-mode) below.
 
 > Note: it's important to instruct the model to use JSON in the `prompt`. Otherwise, the model may generate large amounts whitespace.
 
@@ -90,7 +90,7 @@ The final response in the stream also includes additional data about the generat
 - `load_duration`: time spent in nanoseconds loading the model
 - `prompt_eval_count`: number of tokens in the prompt
 - `prompt_eval_duration`: time spent in nanoseconds evaluating the prompt
-- `eval_count`: number of tokens the response
+- `eval_count`: number of tokens in the response
 - `eval_duration`: time in nanoseconds spent generating the response
 - `context`: an encoding of the conversation used in this response, this can be sent in the next request to keep a conversational memory
 - `response`: empty if the response was streamed, if not streamed, this will contain the full response
@@ -256,9 +256,9 @@ For reproducible outputs, set `temperature` to 0 and `seed` to a number:
 ```shell
 curl http://localhost:11434/api/generate -d '{
   "model": "mistral",
-  "prompt": "[INST] why is the sky blue? [/INST]",
+  "prompt": "Why is the sky blue?",
   "options": {
-    "seed": 101,
+    "seed": 123,
     "temperature": 0
   }
 }'
@@ -321,7 +321,6 @@ curl http://localhost:11434/api/generate -d '{
     "vocab_only": false,
     "use_mmap": true,
     "use_mlock": false,
-    "embedding_only": false,
     "rope_frequency_base": 1.1,
     "rope_frequency_scale": 0.8,
     "num_thread": 8
@@ -395,7 +394,6 @@ Advanced parameters (optional):
 
 - `format`: the format to return a response in. Currently the only accepted value is `json`
 - `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
-- `template`: the prompt template to use (overrides what is defined in the `Modelfile`)
 - `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
 - `keep_alive`: controls how long the model will stay loaded into memory following the request (default: `5m`)
 
@@ -1012,7 +1010,8 @@ Generate embeddings from a model
 ### Parameters
 
 - `model`: name of model to generate embeddings from
-- `prompt`: text to generate embeddings for
+- `prompt`: string to generate the embedding for
+- `prompts`: array of strings to generate a batch of embeddings for
 
 Advanced parameters:
 
@@ -1025,7 +1024,7 @@ Advanced parameters:
 
 ```shell
 curl http://localhost:11434/api/embeddings -d '{
-  "model": "llama2",
+  "model": "all-minilm",
   "prompt": "Here is an article about llamas..."
 }'
 ```
@@ -1040,3 +1039,33 @@ curl http://localhost:11434/api/embeddings -d '{
   ]
 }
 ```
+
+
+#### Request (batch)
+
+```shell
+curl http://localhost:11434/api/embeddings -d '{
+  "model": "all-minilm",
+  "prompt_batch": [
+    "Here is an article about llamas...",
+    "Here is another article about llamas..."
+  ]
+}'
+```
+
+#### Response
+
+```json
+{
+  "embedding_batch": [
+    [
+      0.5670403838157654, 0.009260174818336964, 0.23178744316101074, -0.2916173040866852, -0.8924556970596313,
+      0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
+    ],
+    [
+      0.5670403838157654, 0.009260174818336964, 0.23178744316101074, -0.2916173040866852, -0.8924556970596313,
+      0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
+    ],
+  ]
+}
+```

docs/development.md

@@ -3,7 +3,7 @@
 Install required tools:
 
 - cmake version 3.24 or higher
-- go version 1.21 or higher
+- go version 1.22 or higher
 - gcc version 11.4.0 or higher
 
 ```bash
@@ -42,15 +42,15 @@ Now you can run `ollama`:
 
 #### Linux CUDA (NVIDIA)
 
-*Your operating system distribution may already have packages for NVIDIA CUDA. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!*
+_Your operating system distribution may already have packages for NVIDIA CUDA. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
 
 Install `cmake` and `golang` as well as [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads)
-development and runtime packages. 
+development and runtime packages.
 
 Typically the build scripts will auto-detect CUDA, however, if your Linux distro
 or installation approach uses unusual paths, you can specify the location by
 specifying an environment variable `CUDA_LIB_DIR` to the location of the shared
-libraries, and `CUDACXX` to the location of the nvcc compiler.  You can customize
+libraries, and `CUDACXX` to the location of the nvcc compiler. You can customize
 set set of target CUDA architectues by setting `CMAKE_CUDA_ARCHITECTURES` (e.g. "50;60;70")
 
 Then generate dependencies:
@@ -67,15 +67,15 @@ go build .
 
 #### Linux ROCm (AMD)
 
-*Your operating system distribution may already have packages for AMD ROCm and CLBlast. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!*
+_Your operating system distribution may already have packages for AMD ROCm and CLBlast. Distro packages are often preferable, but instructions are distro-specific. Please consult distro-specific docs for dependencies if available!_
 
-Install [CLBlast](https://github.com/CNugteren/CLBlast/blob/master/doc/installation.md) and [ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) developement packages first, as well as `cmake` and `golang`.
+Install [CLBlast](https://github.com/CNugteren/CLBlast/blob/master/doc/installation.md) and [ROCm](https://rocm.docs.amd.com/en/latest/) development packages first, as well as `cmake` and `golang`.
 
 Typically the build scripts will auto-detect ROCm, however, if your Linux distro
 or installation approach uses unusual paths, you can specify the location by
 specifying an environment variable `ROCM_PATH` to the location of the ROCm
 install (typically `/opt/rocm`), and `CLBlast_DIR` to the location of the
-CLBlast install (typically `/usr/lib/cmake/CLBlast`).  You can also customize
+CLBlast install (typically `/usr/lib/cmake/CLBlast`). You can also customize
 the AMD GPU targets by setting AMDGPU_TARGETS (e.g. `AMDGPU_TARGETS="gfx1101;gfx1102"`)
 
 ```
@@ -88,17 +88,17 @@ Then build the binary:
 go build .
 ```
 
-ROCm requires elevated privileges to access the GPU at runtime.  On most distros you can add your user account to the `render` group, or run as root.
+ROCm requires elevated privileges to access the GPU at runtime. On most distros you can add your user account to the `render` group, or run as root.
 
 #### Advanced CPU Settings
 
 By default, running `go generate ./...` will compile a few different variations
 of the LLM library based on common CPU families and vector math capabilities,
 including a lowest-common-denominator which should run on almost any 64 bit CPU
-somewhat slowly.  At runtime, Ollama will auto-detect the optimal variation to
-load.  If you would like to build a CPU-based build customized for your
+somewhat slowly. At runtime, Ollama will auto-detect the optimal variation to
+load. If you would like to build a CPU-based build customized for your
 processor, you can set `OLLAMA_CUSTOM_CPU_DEFS` to the llama.cpp flags you would
-like to use.  For example, to compile an optimized binary for an Intel i9-9880H,
+like to use. For example, to compile an optimized binary for an Intel i9-9880H,
 you might use:
 
 ```
@@ -108,8 +108,7 @@ go build .
 
 #### Containerized Linux Build
 
-If you have Docker available, you can build linux binaries with `./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included.  The resulting binary is placed in `./dist`
-
+If you have Docker available, you can build linux binaries with `./scripts/build_linux.sh` which has the CUDA and ROCm dependencies included. The resulting binary is placed in `./dist`
 
 ### Windows
 
@@ -118,21 +117,29 @@ Note: The windows build for Ollama is still under development.
 Install required tools:
 
 - MSVC toolchain - C/C++ and cmake as minimal requirements
-- go version 1.21 or higher
+- Go version 1.22 or higher
 - MinGW (pick one variant) with GCC.
-  - <https://www.mingw-w64.org/>
-  - <https://www.msys2.org/>
+  - [MinGW-w64](https://www.mingw-w64.org/)
+  - [MSYS2](https://www.msys2.org/)
 
 ```powershell
 $env:CGO_ENABLED="1"
-
 go generate ./...
-
 go build .
 ```
 
 #### Windows CUDA (NVIDIA)
 
-In addition to the common Windows development tools described above, install:
+In addition to the common Windows development tools described above, install CUDA after installing MSVC.
 
 - [NVIDIA CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html)
+
+
+#### Windows ROCm (AMD Radeon)
+
+In addition to the common Windows development tools described above, install AMDs HIP package after installing MSVC.
+
+- [AMD HIP](https://www.amd.com/en/developer/resources/rocm-hub/hip-sdk.html)
+- [Strawberry Perl](https://strawberryperl.com/)
+
+Lastly, add `ninja.exe` included with MSVC to the system path (e.g. `C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\Common7\IDE\CommonExtensions\Microsoft\CMake\Ninja`).

docs/faq.md

@@ -14,6 +14,10 @@ curl -fsSL https://ollama.com/install.sh | sh
 
 Review the [Troubleshooting](./troubleshooting.md) docs for more about using logs.
 
+## Is my GPU compatible with Ollama?
+
+Please refer to the [GPU docs](./gpu.md).
+
 ## How can I specify the context window size?
 
 By default, Ollama uses a context window size of 2048 tokens.
@@ -95,6 +99,37 @@ Ollama binds 127.0.0.1 port 11434 by default. Change the bind address with the `
 
 Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
 
+## How can I use Ollama with a proxy server?
+
+Ollama runs an HTTP server and can be exposed using a proxy server such as Nginx. To do so, configure the proxy to forward requests and optionally set required headers (if not exposing Ollama on the network). For example, with Nginx:
+
+```
+server {
+    listen 80;
+    server_name example.com;  # Replace with your domain or IP
+    location / {
+        proxy_pass http://localhost:11434;
+        proxy_set_header Host localhost:11434;
+    }
+}
+```
+
+## How can I use Ollama with ngrok?
+
+Ollama can be accessed using a range of tools for tunneling tools. For example with Ngrok:
+
+```
+ngrok http 11434 --host-header="localhost:11434"
+```
+
+## How can I use Ollama with Cloudflare Tunnel?
+
+To use Ollama with Cloudflare Tunnel, use the `--url` and `--http-host-header` flags:
+
+```
+cloudflared tunnel --url http://localhost:11434 --http-host-header="localhost:11434"
+```
+
 ## How can I allow additional web origins to access Ollama?
 
 Ollama allows cross-origin requests from `127.0.0.1` and `0.0.0.0` by default. Additional origins can be configured with `OLLAMA_ORIGINS`.
@@ -113,13 +148,13 @@ If a different directory needs to be used, set the environment variable `OLLAMA_
 
 Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
 
-## Does Ollama send my prompts and answers back to Ollama.ai to use in any way?
+## Does Ollama send my prompts and answers back to ollama.com?
 
-No, Ollama runs entirely locally, and conversation data will never leave your machine.
+No. Ollama runs locally, and conversation data does not leave your machine.
 
 ## How can I use Ollama in Visual Studio Code?
 
-There is already a large collection of plugins available for VSCode as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/jmorganca/ollama#extensions--plugins) at the bottom of the main repository readme.
+There is already a large collection of plugins available for VSCode as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/ollama/ollama#extensions--plugins) at the bottom of the main repository readme.
 
 ## How do I use Ollama behind a proxy?
 
@@ -193,3 +228,7 @@ To unload the model and free up memory use:
 ```shell
 curl http://localhost:11434/api/generate -d '{"model": "llama2", "keep_alive": 0}'
 ```
+
+Alternatively, you can change the amount of time all models are loaded into memory by setting the `OLLAMA_KEEP_ALIVE` environment variable when starting the Ollama server. The `OLLAMA_KEEP_ALIVE` variable uses the same parameter types as the `keep_alive` parameter types mentioned above. Refer to section explaining [how to configure the Ollama server](#how-do-i-configure-ollama-server) to correctly set the environment variable.
+
+If you wish to override the `OLLAMA_KEEP_ALIVE` setting, use the `keep_alive` API parameter with the `/api/generate` or `/api/chat` API endpoints.

docs/gpu.md

@@ -0,0 +1,102 @@
+# GPU
+## Nvidia
+Ollama supports Nvidia GPUs with compute capability 5.0+.
+
+Check your compute compatibility to see if your card is supported:
+[https://developer.nvidia.com/cuda-gpus](https://developer.nvidia.com/cuda-gpus)
+
+| Compute Capability | Family              | Cards                                                                                                       |
+| ------------------ | ------------------- | ----------------------------------------------------------------------------------------------------------- |
+| 9.0                | NVIDIA              | `H100`                                                                                                      |
+| 8.9                | GeForce RTX 40xx    | `RTX 4090` `RTX 4080` `RTX 4070 Ti` `RTX 4060 Ti`                                                           |
+|                    | NVIDIA Professional | `L4` `L40` `RTX 6000`                                                                                       |
+| 8.6                | GeForce RTX 30xx    | `RTX 3090 Ti` `RTX 3090` `RTX 3080 Ti` `RTX 3080` `RTX 3070 Ti` `RTX 3070` `RTX 3060 Ti` `RTX 3060`         |
+|                    | NVIDIA Professional | `A40` `RTX A6000` `RTX A5000` `RTX A4000` `RTX A3000` `RTX A2000` `A10` `A16` `A2`                          |
+| 8.0                | NVIDIA              | `A100` `A30`                                                                                                |
+| 7.5                | GeForce GTX/RTX     | `GTX 1650 Ti` `TITAN RTX` `RTX 2080 Ti` `RTX 2080` `RTX 2070` `RTX 2060`                                    |
+|                    | NVIDIA Professional | `T4` `RTX 5000` `RTX 4000` `RTX 3000` `T2000` `T1200` `T1000` `T600` `T500`                                 |
+|                    | Quadro              | `RTX 8000` `RTX 6000` `RTX 5000` `RTX 4000`                                                                 |
+| 7.0                | NVIDIA              | `TITAN V` `V100` `Quadro GV100`                                                                             |
+| 6.1                | NVIDIA TITAN        | `TITAN Xp` `TITAN X`                                                                                        |
+|                    | GeForce GTX         | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050`                                     |
+|                    | Quadro              | `P6000` `P5200` `P4200` `P3200` `P5000` `P4000` `P3000` `P2200` `P2000` `P1000` `P620` `P600` `P500` `P520` |
+|                    | Tesla               | `P40` `P4`                                                                                                  |
+| 6.0                | NVIDIA              | `Tesla P100` `Quadro GP100`                                                                                 |
+| 5.2                | GeForce GTX         | `GTX TITAN X` `GTX 980 Ti` `GTX 980` `GTX 970` `GTX 960` `GTX 950`                                          |
+|                    | Quadro              | `M6000 24GB` `M6000` `M5000` `M5500M` `M4000` `M2200` `M2000` `M620`                                        |
+|                    | Tesla               | `M60` `M40`                                                                                                 |
+| 5.0                | GeForce GTX         | `GTX 750 Ti` `GTX 750` `NVS 810`                                                                            |
+|                    | Quadro              | `K2200` `K1200` `K620` `M1200` `M520` `M5000M` `M4000M` `M3000M` `M2000M` `M1000M` `K620M` `M600M` `M500M`  |
+
+
+### GPU Selection
+
+If you have multiple NVIDIA GPUs in your system and want to limit Ollama to use
+a subset, you can set `CUDA_VISIBLE_DEVICES` to a comma separated list of GPUs.
+Numeric IDs may be used, however ordering may vary, so UUIDs are more reliable.
+You can discover the UUID of your GPUs by running `nvidia-smi -L` If you want to
+ignore the GPUs and force CPU usage, use an invalid GPU ID (e.g., "-1")
+
+### Laptop Suspend Resume
+
+On linux, after a suspend/resume cycle, sometimes Ollama will fail to discover
+your NVIDIA GPU, and fallback to running on the CPU.  You can workaround this
+driver bug by reloading the NVIDIA UVM driver with `sudo rmmod nvidia_uvm &&
+sudo modprobe nvidia_uvm`
+
+## AMD Radeon
+Ollama supports the following AMD GPUs:
+| Family         | Cards and accelerators                                                                                                               |
+| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
+| AMD Radeon RX  | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` `Vega 64` `Vega 56`    |
+| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` `V420` `V340` `V320` `Vega II Duo` `Vega II` `VII` `SSG` |
+| AMD Instinct   | `MI300X` `MI300A` `MI300` `MI250X` `MI250` `MI210` `MI200` `MI100` `MI60` `MI50`                                                               |
+
+### Overrides
+Ollama leverages the AMD ROCm library, which does not support all AMD GPUs. In
+some cases you can force the system to try to use a similar LLVM target that is
+close.  For example The Radeon RX 5400 is `gfx1034` (also known as 10.3.4)
+however, ROCm does not currently support this target. The closest support is
+`gfx1030`.  You can use the environment variable `HSA_OVERRIDE_GFX_VERSION` with
+`x.y.z` syntax.  So for example, to force the system to run on the RX 5400, you
+would set `HSA_OVERRIDE_GFX_VERSION="10.3.0"` as an environment variable for the
+server.  If you have an unsupported AMD GPU you can experiment using the list of
+supported types below.
+
+At this time, the known supported GPU types are the following LLVM Targets.
+This table shows some example GPUs that map to these LLVM targets:
+| **LLVM Target** | **An Example GPU** |
+|-----------------|---------------------|
+| gfx900 | Radeon RX Vega 56 |
+| gfx906 | Radeon Instinct MI50 |
+| gfx908 | Radeon Instinct MI100 |
+| gfx90a | Radeon Instinct MI210 |
+| gfx940 | Radeon Instinct MI300 |
+| gfx941 | |
+| gfx942 | |
+| gfx1030 | Radeon PRO V620 |
+| gfx1100 | Radeon PRO W7900 |
+| gfx1101 | Radeon PRO W7700 |
+| gfx1102 | Radeon RX 7600 |
+
+AMD is working on enhancing ROCm v6 to broaden support for families of GPUs in a
+future release which should increase support for more GPUs.
+
+Reach out on [Discord](https://discord.gg/ollama) or file an
+[issue](https://github.com/ollama/ollama/issues) for additional help.
+
+### GPU Selection
+
+If you have multiple AMD GPUs in your system and want to limit Ollama to use a
+subset, you can set `HIP_VISIBLE_DEVICES` to a comma separated list of GPUs.
+You can see the list of devices with `rocminfo`.  If you want to ignore the GPUs
+and force CPU usage, use an invalid GPU ID (e.g., "-1")
+
+### Container Permission
+
+In some Linux distributions, SELinux can prevent containers from
+accessing the AMD GPU devices.  On the host system you can run 
+`sudo setsebool container_use_devices=1` to allow containers to use devices.
+
+### Metal (Apple GPUs)
+Ollama supports GPU acceleration on Apple devices via the Metal API.

docs/import.md

@@ -124,7 +124,10 @@ ollama run example "What is your favourite condiment?"
 Publishing models is in early alpha. If you'd like to publish your model to share with others, follow these steps:
 
 1. Create [an account](https://ollama.com/signup)
-2. Run `cat ~/.ollama/id_ed25519.pub` (or `type %USERPROFILE%\.ollama\id_ed25519.pub` on Windows) to view your Ollama public key. Copy this to the clipboard.
+2. Copy your Ollama public key:
+  - macOS: `cat ~/.ollama/id_ed25519.pub`
+  - Windows: `type %USERPROFILE%\.ollama\id_ed25519.pub`
+  - Linux: `cat /usr/share/ollama/.ollama/id_ed25519.pub`
 3. Add your public key to your [Ollama account](https://ollama.com/settings/keys)
 
 Next, copy your model to your username's namespace:

docs/linux.md

@@ -10,6 +10,14 @@ Install Ollama running this one-liner:
 curl -fsSL https://ollama.com/install.sh | sh
 ```
 
+## AMD Radeon GPU support
+
+While AMD has contributed the `amdgpu` driver upstream to the official linux
+kernel source, the version is older and may not support all ROCm features. We
+recommend you install the latest driver from
+https://www.amd.com/en/support/linux-drivers for best support of your Radeon
+GPU.
+
 ## Manual install
 
 ### Download the `ollama` binary
@@ -64,6 +72,11 @@ Verify that the drivers are installed by running the following command, which sh
 nvidia-smi
 ```
 
+### Install ROCm (optional - for Radeon GPUs)
+[Download and Install](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html)
+
+Make sure to install ROCm v6
+
 ### Start Ollama
 
 Start Ollama using `systemd`:

docs/modelfile.md

@@ -113,7 +113,7 @@ FROM llama2
 ```
 
 A list of available base models:
-<https://github.com/jmorganca/ollama#model-library>
+<https://github.com/ollama/ollama#model-library>
 
 #### Build from a `bin` file
 
@@ -131,7 +131,7 @@ The `PARAMETER` instruction defines a parameter that can be set when the model i
 PARAMETER <parameter> <parametervalue>
 ```
 
-### Valid Parameters and Values
+#### Valid Parameters and Values
 
 | Parameter      | Description                                                                                                                                                                                                                                             | Value Type | Example Usage        |
 | -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | -------------------- |
@@ -139,9 +139,6 @@ PARAMETER <parameter> <parametervalue>
 | mirostat_eta   | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)                        | float      | mirostat_eta 0.1     |
 | mirostat_tau   | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)                                                                                                         | float      | mirostat_tau 5.0     |
 | num_ctx        | Sets the size of the context window used to generate the next token. (Default: 2048)                                                                                                                                                                    | int        | num_ctx 4096         |
-| num_gqa        | The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b                                                                                                                                         | int        | num_gqa 1            |
-| num_gpu        | The number of layers to send to the GPU(s). On macOS it defaults to 1 to enable metal support, 0 to disable.                                                                                                                                            | int        | num_gpu 50           |
-| num_thread     | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores). | int        | num_thread 8         |
 | repeat_last_n  | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)                                                                                                                                           | int        | repeat_last_n 64     |
 | repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)                                                                     | float      | repeat_penalty 1.1   |
 | temperature    | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)                                                                                                                                     | float      | temperature 0.7      |
@@ -183,7 +180,7 @@ SYSTEM """<system message>"""
 
 ### ADAPTER
 
-The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be tuned from the base model otherwise the behaviour is undefined.
+The `ADAPTER` instruction is an optional instruction that specifies any LoRA adapter that should apply to the base model. The value of this instruction should be an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be tuned from the base model otherwise the behaviour is undefined.
 
 ```modelfile
 ADAPTER ./ollama-lora.bin
@@ -201,7 +198,22 @@ LICENSE """
 
 ### MESSAGE
 
-The `MESSAGE` instruction allows you to specify a message history for the model to use when responding:
+The `MESSAGE` instruction allows you to specify a message history for the model to use when responding. Use multiple iterations of the MESSAGE command to build up a conversation which will guide the model to answer in a similar way.
+
+```modelfile
+MESSAGE <role> <message>
+```
+
+#### Valid roles
+
+| Role      | Description                                                  |
+| --------- | ------------------------------------------------------------ |
+| system    | Alternate way of providing the SYSTEM message for the model. |
+| user      | An example message of what the user could have asked.        |
+| assistant | An example message of how the model should respond.          |
+
+
+#### Example conversation
 
 ```modelfile
 MESSAGE user Is Toronto in Canada?
@@ -212,6 +224,7 @@ MESSAGE user Is Ontario in Canada?
 MESSAGE assistant yes
 ```
 
+
 ## Notes
 
 - the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to distinguish it from arguments.

docs/openai.md

@@ -1,6 +1,6 @@
 # OpenAI compatibility
 
-> **Note:** OpenAI compatibility is experimental and is subject to major adjustments including breaking changes. For fully-featured access to the Ollama API, see the Ollama [Python library](https://github.com/ollama/ollama-python), [JavaScript library](https://github.com/ollama/ollama-js) and [REST API](https://github.com/jmorganca/ollama/blob/main/docs/api.md).
+> **Note:** OpenAI compatibility is experimental and is subject to major adjustments including breaking changes. For fully-featured access to the Ollama API, see the Ollama [Python library](https://github.com/ollama/ollama-python), [JavaScript library](https://github.com/ollama/ollama-js) and [REST API](https://github.com/ollama/ollama/blob/main/docs/api.md).
 
 Ollama provides experimental compatibility with parts of the [OpenAI API](https://platform.openai.com/docs/api-reference) to help connect existing applications to Ollama.
 

docs/troubleshooting.md

@@ -67,6 +67,19 @@ You can see what features your CPU has with the following.
 cat /proc/cpuinfo| grep flags  | head -1
 ```
 
-## Known issues
+## Installing older or pre-release versions on Linux
 
-* N/A
+If you run into problems on Linux and want to install an older version, or you'd
+like to try out a pre-release before it's officially released, you can tell the
+install script which version to install.
+
+```sh
+curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION="0.1.29" sh
+```
+
+## Linux tmp noexec 
+
+If your system is configured with the "noexec" flag where Ollama stores its
+temporary executable files, you can specify an alternate location by setting
+OLLAMA_TMPDIR to a location writable by the user ollama runs as.  For example
+OLLAMA_TMPDIR=/usr/share/ollama/

docs/tutorials/langchainjs.md

@@ -18,7 +18,7 @@ const ollama = new Ollama({
   model: "llama2",
 });
 
-const answer = await ollama.call(`why is the sky blue?`);
+const answer = await ollama.invoke(`why is the sky blue?`);
 
 console.log(answer);
 ```

docs/tutorials/langchainpy.md

@@ -42,12 +42,12 @@ text_splitter=RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=0)
 all_splits = text_splitter.split_documents(data)
 ```
 
-It's split up, but we have to find the relevant splits and then submit those to the model. We can do this by creating embeddings and storing them in a vector database. We can use Ollama directly to instantiate an embedding model. We will use ChromaDB in this example for a vector database. `pip install GPT4All chromadb`
+It's split up, but we have to find the relevant splits and then submit those to the model. We can do this by creating embeddings and storing them in a vector database. We can use Ollama directly to instantiate an embedding model. We will use ChromaDB in this example for a vector database. `pip install chromadb`
 
 ```python
 from langchain.embeddings import OllamaEmbeddings
 from langchain.vectorstores import Chroma
-oembed = OllamaEmbeddings(base_url="http://localhost:11434", model="llama2")
+oembed = OllamaEmbeddings(base_url="http://localhost:11434", model="nomic-embed-text")
 vectorstore = Chroma.from_documents(documents=all_splits, embedding=oembed)
 ```
 
@@ -66,7 +66,7 @@ The next thing is to send the question and the relevant parts of the docs to the
 ```python
 from langchain.chains import RetrievalQA
 qachain=RetrievalQA.from_chain_type(ollama, retriever=vectorstore.as_retriever())
-qachain({"query": question})
+qachain.invoke({"query": question})
 ```
 
 The answer received from this chain was:

docs/tutorials/nvidia-jetson.md

@@ -1,38 +1,15 @@
 # Running Ollama on NVIDIA Jetson Devices
 
-With some minor configuration, Ollama runs well on [NVIDIA Jetson Devices](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/). The following has been tested on [JetPack 5.1.2](https://developer.nvidia.com/embedded/jetpack).
+Ollama runs well on [NVIDIA Jetson Devices](https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/) and should run out of the box with the standard installation instructions. 
 
-NVIDIA Jetson devices are Linux-based embedded AI computers that are purpose-built for AI applications.
-
-Jetsons have an integrated GPU that is wired directly to the memory controller of the machine. For this reason, the `nvidia-smi` command is unrecognized, and Ollama proceeds to operate in "CPU only"
-mode. This can be verified by using a monitoring tool like jtop.
-
-In order to address this, we simply pass the path to the Jetson's pre-installed CUDA libraries into `ollama serve` (while in a tmux session). We then hardcode the num_gpu parameters into a cloned
-version of our target model.
-
-Prerequisites:
-
-- curl
-- tmux
-
-Here are the steps:
+The following has been tested on [JetPack 5.1.2](https://developer.nvidia.com/embedded/jetpack), but should also work on JetPack 6.0.
 
 - Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.com/install.sh | sh`
-- Stop the Ollama service: `sudo systemctl stop ollama`
-- Start Ollama serve in a tmux session called ollama_jetson and reference the CUDA libraries path: `tmux has-session -t ollama_jetson 2>/dev/null || tmux new-session -d -s ollama_jetson 
-'LD_LIBRARY_PATH=/usr/local/cuda/lib64 ollama serve'`
 - Pull the model you want to use (e.g. mistral): `ollama pull mistral`
-- Create a new Modelfile specifically for enabling GPU support on the Jetson: `touch ModelfileMistralJetson`
-- In the ModelfileMistralJetson file, specify the FROM model and the num_gpu PARAMETER as shown below:
-
-```
-FROM mistral
-PARAMETER num_gpu 999
-```
-
-- Create a new model from your Modelfile: `ollama create mistral-jetson -f ./ModelfileMistralJetson`
-- Run the new model: `ollama run mistral-jetson`
-
-If you run a monitoring tool like jtop you should now see that Ollama is using the Jetson's integrated GPU.
+- Start an interactive session: `ollama run mistral`
 
 And that's it!
+
+# Running Ollama in Docker
+
+When running GPU accelerated applications in Docker, it is highly recommended to use [dusty-nv jetson-containers repo](https://github.com/dusty-nv/jetson-containers).

docs/windows.md

@@ -4,7 +4,7 @@ Welcome to the Ollama Windows preview.
 
 No more WSL required!
 
-Ollama now runs as a native Windows application, including NVIDIA GPU support.
+Ollama now runs as a native Windows application, including NVIDIA and AMD Radeon GPU support.
 After installing Ollama Windows Preview, Ollama will run in the background and
 the `ollama` command line is available in `cmd`, `powershell` or your favorite
 terminal application. As usual the Ollama [api](./api.md) will be served on
@@ -14,13 +14,14 @@ As this is a preview release, you should expect a few bugs here and there.  If
 you run into a problem you can reach out on
 [Discord](https://discord.gg/ollama), or file an 
 [issue](https://github.com/ollama/ollama/issues).
-Logs will often be helpful in dianosing the problem (see
+Logs will often be helpful in diagnosing the problem (see
 [Troubleshooting](#troubleshooting) below)
 
 ## System Requirements
 
 * Windows 10 or newer, Home or Pro
 * NVIDIA 452.39 or newer Drivers if you have an NVIDIA card
+* AMD Radeon Driver https://www.amd.com/en/support if you have a Radeon card
 
 ## API Access
 

examples/go-chat/main.go

@@ -0,0 +1,51 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"log"
+
+	"github.com/ollama/ollama/api"
+)
+
+func main() {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	messages := []api.Message{
+		api.Message{
+			Role:    "system",
+			Content: "Provide very brief, concise responses",
+		},
+		api.Message{
+			Role:    "user",
+			Content: "Name some unusual animals",
+		},
+		api.Message{
+			Role:    "assistant",
+			Content: "Monotreme, platypus, echidna",
+		},
+		api.Message{
+			Role:    "user",
+			Content: "which of these is the most dangerous?",
+		},
+	}
+
+	ctx := context.Background()
+	req := &api.ChatRequest{
+		Model:    "llama2",
+		Messages: messages,
+	}
+
+	respFunc := func(resp api.ChatResponse) error {
+		fmt.Print(resp.Message.Content)
+		return nil
+	}
+
+	err = client.Chat(ctx, req, respFunc)
+	if err != nil {
+		log.Fatal(err)
+	}
+}

examples/go-generate-streaming/main.go

@@ -0,0 +1,40 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"log"
+
+	"github.com/ollama/ollama/api"
+)
+
+func main() {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	// By default, GenerateRequest is streaming.
+	req := &api.GenerateRequest{
+		Model:  "gemma",
+		Prompt: "how many planets are there?",
+	}
+
+	ctx := context.Background()
+	respFunc := func(resp api.GenerateResponse) error {
+		// Only print the response here; GenerateResponse has a number of other
+		// interesting fields you want to examine.
+
+		// In streaming mode, responses are partial so we call fmt.Print (and not
+		// Println) in order to avoid spurious newlines being introduced. The
+		// model will insert its own newlines if it wants.
+		fmt.Print(resp.Response)
+		return nil
+	}
+
+	err = client.Generate(ctx, req, respFunc)
+	if err != nil {
+		log.Fatal(err)
+	}
+	fmt.Println()
+}

examples/go-generate/main.go

@@ -0,0 +1,37 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"log"
+
+	"github.com/ollama/ollama/api"
+)
+
+func main() {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	req := &api.GenerateRequest{
+		Model:  "gemma",
+		Prompt: "how many planets are there?",
+
+		// set streaming to false
+		Stream: new(bool),
+	}
+
+	ctx := context.Background()
+	respFunc := func(resp api.GenerateResponse) error {
+		// Only print the response here; GenerateResponse has a number of other
+		// interesting fields you want to examine.
+		fmt.Println(resp.Response)
+		return nil
+	}
+
+	err = client.Generate(ctx, req, respFunc)
+	if err != nil {
+		log.Fatal(err)
+	}
+}

examples/go-multimodal/main.go

@@ -0,0 +1,47 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"log"
+	"os"
+
+	"github.com/ollama/ollama/api"
+)
+
+func main() {
+	if len(os.Args) <= 1 {
+		log.Fatal("usage: <image name>")
+	}
+
+	imgData, err := os.ReadFile(os.Args[1])
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	req := &api.GenerateRequest{
+		Model:  "llava",
+		Prompt: "describe this image",
+		Images: []api.ImageData{imgData},
+	}
+
+	ctx := context.Background()
+	respFunc := func(resp api.GenerateResponse) error {
+		// In streaming mode, responses are partial so we call fmt.Print (and not
+		// Println) in order to avoid spurious newlines being introduced. The
+		// model will insert its own newlines if it wants.
+		fmt.Print(resp.Response)
+		return nil
+	}
+
+	err = client.Generate(ctx, req, respFunc)
+	if err != nil {
+		log.Fatal(err)
+	}
+	fmt.Println()
+}

examples/go-pull-progress/main.go

@@ -0,0 +1,31 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"log"
+
+	"github.com/ollama/ollama/api"
+)
+
+func main() {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		log.Fatal(err)
+	}
+
+	ctx := context.Background()
+
+	req := &api.PullRequest{
+		Model: "mistral",
+	}
+	progressFunc := func(resp api.ProgressResponse) error {
+		fmt.Printf("Progress: status=%v, total=%v, completed=%v\n", resp.Status, resp.Total, resp.Completed)
+		return nil
+	}
+
+	err = client.Pull(ctx, req, progressFunc)
+	if err != nil {
+		log.Fatal(err)
+	}
+}

examples/langchain-python-rag-privategpt/README.md

@@ -1,6 +1,6 @@
 # PrivateGPT with Llama 2 uncensored
 
-https://github.com/jmorganca/ollama/assets/3325447/20cf8ec6-ff25-42c6-bdd8-9be594e3ce1b
+https://github.com/ollama/ollama/assets/3325447/20cf8ec6-ff25-42c6-bdd8-9be594e3ce1b
 
 > Note: this example is a slightly modified version of PrivateGPT using models such as Llama 2 Uncensored. All credit for PrivateGPT goes to Iván Martínez who is the creator of it, and you can find his GitHub repo [here](https://github.com/imartinez/privateGPT).
 

examples/modelfile-mario/readme.md

@@ -28,7 +28,7 @@ You are Mario from Super Mario Bros, acting as an assistant.
 What if you want to change its behaviour?
 
 - Try changing the prompt
-- Try changing the parameters [Docs](https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md)
+- Try changing the parameters [Docs](https://github.com/ollama/ollama/blob/main/docs/modelfile.md)
 - Try changing the model (e.g. An uncensored model by `FROM wizard-vicuna` this is the wizard-vicuna uncensored model )
 
 Once the changes are made,

examples/modelfile-tweetwriter/readme.md

@@ -1,23 +0,0 @@
-# Example Modelfile - Tweetwriter
-
-This simple examples shows what you can do without any code, simply relying on a Modelfile. The file has two instructions:
-
-1. FROM - The From instructions defines the parent model to use for this one. If you choose a model from the library, you can enter just the model name. For all other models, you need to specify the namespace as well. You could also use a local file. Just include the relative path to the converted, quantized model weights file. To learn more about creating that file, see the `import.md` file in the docs folder of this repository.
-2. SYSTEM - This defines the system prompt for the model and overrides the system prompt from the parent model.
-
-## Running the Example
-
-1. Create the model:
-
-   ```bash
-   ollama create tweetwriter
-   ```
-
-2. Enter a topic to generate a tweet about.
-3. Show the Modelfile in the REPL.
-
-   ```bash
-   /show modelfile
-   ```
-
-   Notice that the FROM and SYSTEM match what was in the file. But there is also a TEMPLATE and PARAMETER. These are inherited from the parent model.

examples/python-json-datagenerator/readme.md

@@ -1,6 +1,6 @@
 # JSON Output Example
 
-![llmjson 2023-11-10 15_31_31](https://github.com/jmorganca/ollama/assets/633681/e599d986-9b4a-4118-81a4-4cfe7e22da25)
+![llmjson 2023-11-10 15_31_31](https://github.com/ollama/ollama/assets/633681/e599d986-9b4a-4118-81a4-4cfe7e22da25)
 
 There are two python scripts in this example. `randomaddresses.py` generates random addresses from different countries. `predefinedschema.py` sets a template for the model to fill in.
 

examples/python-loganalysis/readme.md

@@ -1,6 +1,6 @@
 # Log Analysis example
 
-![loganalyzer 2023-11-10 08_53_29](https://github.com/jmorganca/ollama/assets/633681/ad30f1fc-321f-4953-8914-e30e24db9921)
+![loganalyzer 2023-11-10 08_53_29](https://github.com/ollama/ollama/assets/633681/ad30f1fc-321f-4953-8914-e30e24db9921)
 
 This example shows one possible way to create a log file analyzer. It uses the model **mattw/loganalyzer** which is based on **codebooga**, a 34b parameter model.
 

examples/typescript-functioncalling/readme.md

@@ -1,6 +1,6 @@
 # Function calling
 
-![function calling 2023-11-16 16_12_58](https://github.com/jmorganca/ollama/assets/633681/a0acc247-9746-45ab-b325-b65dfbbee4fb)
+![function calling 2023-11-16 16_12_58](https://github.com/ollama/ollama/assets/633681/a0acc247-9746-45ab-b325-b65dfbbee4fb)
 
 One of the features added to some models is 'function calling'. It's a bit of a confusing name. It's understandable if you think that means the model can call functions, but that's not what it means. Function calling simply means that the output of the model is formatted in JSON, using a preconfigured schema, and uses the expected types. Then your code can use the output of the model and call functions with it. Using the JSON format in Ollama, you can use any model for function calling. 
 

format/bytes.go

@@ -6,11 +6,16 @@ import (
 )
 
 const (
-	Byte     = 1
+	Byte = 1
+
 	KiloByte = Byte * 1000
 	MegaByte = KiloByte * 1000
 	GigaByte = MegaByte * 1000
 	TeraByte = GigaByte * 1000
+
+	KibiByte = Byte * 1024
+	MebiByte = KibiByte * 1024
+	GibiByte = MebiByte * 1024
 )
 
 func HumanBytes(b int64) string {
@@ -45,3 +50,14 @@ func HumanBytes(b int64) string {
 		return fmt.Sprintf("%d %s", int(value), unit)
 	}
 }
+
+func HumanBytes2(b uint64) string {
+	switch {
+	case b >= MebiByte:
+		return fmt.Sprintf("%.1f MiB", float64(b)/MebiByte)
+	case b >= KibiByte:
+		return fmt.Sprintf("%.1f KiB", float64(b)/KibiByte)
+	default:
+		return fmt.Sprintf("%d B", b)
+	}
+}

format/openssh.go

@@ -1,102 +0,0 @@
-// Copyright 2012 The Go Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style
-// license that can be found in the LICENSE file.
-
-// Code originally from https://go-review.googlesource.com/c/crypto/+/218620
-
-// TODO: replace with upstream once the above change is merged and released.
-
-package format
-
-import (
-	"crypto"
-	"crypto/ed25519"
-	"crypto/rand"
-	"encoding/binary"
-	"encoding/pem"
-	"fmt"
-
-	"golang.org/x/crypto/ssh"
-)
-
-const privateKeyAuthMagic = "openssh-key-v1\x00"
-
-type openSSHEncryptedPrivateKey struct {
-	CipherName string
-	KDFName    string
-	KDFOptions string
-	KeysCount  uint32
-	PubKey     []byte
-	KeyBlocks  []byte
-}
-
-type openSSHPrivateKey struct {
-	Check1  uint32
-	Check2  uint32
-	Keytype string
-	Rest    []byte `ssh:"rest"`
-}
-
-type openSSHEd25519PrivateKey struct {
-	Pub     []byte
-	Priv    []byte
-	Comment string
-	Pad     []byte `ssh:"rest"`
-}
-
-func OpenSSHPrivateKey(key crypto.PrivateKey, comment string) (*pem.Block, error) {
-	var check uint32
-	if err := binary.Read(rand.Reader, binary.BigEndian, &check); err != nil {
-		return nil, err
-	}
-
-	var pk1 openSSHPrivateKey
-	pk1.Check1 = check
-	pk1.Check2 = check
-
-	var w openSSHEncryptedPrivateKey
-	w.KeysCount = 1
-
-	if k, ok := key.(*ed25519.PrivateKey); ok {
-		key = *k
-	}
-
-	switch k := key.(type) {
-	case ed25519.PrivateKey:
-		pub, priv := k[32:], k
-		key := openSSHEd25519PrivateKey{
-			Pub:     pub,
-			Priv:    priv,
-			Comment: comment,
-		}
-
-		pk1.Keytype = ssh.KeyAlgoED25519
-		pk1.Rest = ssh.Marshal(key)
-
-		w.PubKey = ssh.Marshal(struct {
-			KeyType string
-			Pub     []byte
-		}{
-			ssh.KeyAlgoED25519, pub,
-		})
-	default:
-		return nil, fmt.Errorf("ssh: unknown key type %T", k)
-	}
-
-	w.KeyBlocks = openSSHPadding(ssh.Marshal(pk1), 8)
-
-	w.CipherName, w.KDFName, w.KDFOptions = "none", "none", ""
-
-	return &pem.Block{
-		Type:  "OPENSSH PRIVATE KEY",
-		Bytes: append([]byte(privateKeyAuthMagic), ssh.Marshal(w)...),
-	}, nil
-}
-
-func openSSHPadding(block []byte, blocksize int) []byte {
-	for i, j := 0, len(block); (j+i)%blocksize != 0; i++ {
-		block = append(block, byte(i+1))
-	}
-
-	return block
-}

go.mod

@@ -1,36 +1,47 @@
-module github.com/jmorganca/ollama
+module github.com/ollama/ollama
 
-go 1.21
+go 1.22
+
+toolchain go1.22.0
 
 require (
+	github.com/containerd/console v1.0.3
+	github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
 	github.com/emirpasic/gods v1.18.1
 	github.com/gin-gonic/gin v1.9.1
+	github.com/golang/protobuf v1.5.0 // indirect
+	github.com/google/uuid v1.0.0
+	github.com/mitchellh/mapstructure v1.5.0
 	github.com/olekukonko/tablewriter v0.0.5
 	github.com/spf13/cobra v1.7.0
 	github.com/stretchr/testify v1.8.4
+	github.com/x448/float16 v0.8.4
 	golang.org/x/sync v0.3.0
 )
 
 require (
-	github.com/containerd/console v1.0.3 // indirect
-	github.com/cratonica/2goarray v0.0.0-20190331194516-514510793eaa // indirect
-	github.com/davecgh/go-spew v1.1.1 // indirect
-	github.com/getlantern/context v0.0.0-20190109183933-c447772a6520 // indirect
-	github.com/getlantern/errors v0.0.0-20190325191628-abdb3e3e36f7 // indirect
-	github.com/getlantern/golog v0.0.0-20190830074920-4ef2e798c2d7 // indirect
-	github.com/getlantern/hex v0.0.0-20190417191902-c6586a6fe0b7 // indirect
-	github.com/getlantern/hidden v0.0.0-20190325191715-f02dbb02be55 // indirect
-	github.com/getlantern/ops v0.0.0-20190325191751-d70cb0d6f85f // indirect
-	github.com/getlantern/systray v1.2.2 // indirect
-	github.com/go-stack/stack v1.8.0 // indirect
-	github.com/google/uuid v1.0.0 // indirect
-	github.com/mattn/go-runewidth v0.0.14 // indirect
-	github.com/oxtoacart/bpool v0.0.0-20190530202638-03653db5a59c // indirect
-	github.com/pborman/uuid v1.2.1 // indirect
-	github.com/pmezard/go-difflib v1.0.0 // indirect
-	github.com/rivo/uniseg v0.2.0 // indirect
+	github.com/nlpodyssey/gopickle v0.3.0
+	github.com/pdevine/tensor v0.0.0-20240228013915-64ccaa8d9ca9
 )
 
+require (
+	github.com/apache/arrow/go/arrow v0.0.0-20201229220542-30ce2eb5d4dc // indirect
+	github.com/chewxy/hm v1.0.0 // indirect
+	github.com/chewxy/math32 v1.0.8 // indirect
+	github.com/davecgh/go-spew v1.1.1 // indirect
+	github.com/gogo/protobuf v1.3.2 // indirect
+	github.com/google/flatbuffers v1.12.0 // indirect
+	github.com/mattn/go-runewidth v0.0.14 // indirect
+	github.com/pkg/errors v0.9.1 // indirect
+	github.com/pmezard/go-difflib v1.0.0 // indirect
+	github.com/rivo/uniseg v0.2.0 // indirect
+	github.com/xtgo/set v1.0.0 // indirect
+	go4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect
+	golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1 // indirect
+	gonum.org/v1/gonum v0.8.2 // indirect
+	gorgonia.org/vecf32 v0.9.0 // indirect
+	gorgonia.org/vecf64 v0.9.0 // indirect
+)
 
 require (
 	github.com/bytedance/sonic v1.9.1 // indirect
@@ -50,7 +61,6 @@ require (
 	github.com/mattn/go-isatty v0.0.19 // indirect
 	github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
 	github.com/modern-go/reflect2 v1.0.2 // indirect
-	github.com/pbnjay/memory v0.0.0-20210728143218-7b4eea64cf58
 	github.com/pelletier/go-toml/v2 v2.0.8 // indirect
 	github.com/spf13/pflag v1.0.5 // indirect
 	github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
@@ -61,7 +71,7 @@ require (
 	golang.org/x/net v0.17.0 // indirect
 	golang.org/x/sys v0.13.0
 	golang.org/x/term v0.13.0
-	golang.org/x/text v0.13.0 // indirect
-	google.golang.org/protobuf v1.30.0 // indirect
+	golang.org/x/text v0.14.0 // indirect
+	google.golang.org/protobuf v1.30.0
 	gopkg.in/yaml.v3 v3.0.1 // indirect
 )

go.sum

@@ -1,36 +1,40 @@
+cloud.google.com/go v0.26.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw=
+github.com/BurntSushi/toml v0.3.1/go.mod h1:xHWCNGjB5oqiDr8zfno3MHue2Ht5sIBksp03qcyfWMU=
+github.com/ajstarks/svgo v0.0.0-20180226025133-644b8db467af/go.mod h1:K08gAheRH3/J6wwsYMMT4xOr94bZjxIelGM0+d/wbFw=
+github.com/apache/arrow/go/arrow v0.0.0-20201229220542-30ce2eb5d4dc h1:zvQ6w7KwtQWgMQiewOF9tFtundRMVZFSAksNV6ogzuY=
+github.com/apache/arrow/go/arrow v0.0.0-20201229220542-30ce2eb5d4dc/go.mod h1:c9sxoIT3YgLxH4UhLOCKaBlEojuMhVYpk4Ntv3opUTQ=
 github.com/bytedance/sonic v1.5.0/go.mod h1:ED5hyg4y6t3/9Ku1R6dU/4KyJ48DZ4jPhfY1O2AihPM=
 github.com/bytedance/sonic v1.9.1 h1:6iJ6NqdoxCDr6mbY8h18oSO+cShGSMRGCEo7F2h0x8s=
 github.com/bytedance/sonic v1.9.1/go.mod h1:i736AoUSYt75HyZLoJW9ERYxcy6eaN6h4BZXU064P/U=
+github.com/census-instrumentation/opencensus-proto v0.2.1/go.mod h1:f6KPmirojxKA12rnyqOA5BBL4O983OfeGPqjHWSTneU=
 github.com/chenzhuoyu/base64x v0.0.0-20211019084208-fb5309c8db06/go.mod h1:DH46F32mSOjUmXrMHnKwZdA8wcEefY7UVqBKYGjpdQY=
 github.com/chenzhuoyu/base64x v0.0.0-20221115062448-fe3a3abad311 h1:qSGYFH7+jGhDF8vLC+iwCD4WpbV1EBDSzWkJODFLams=
 github.com/chenzhuoyu/base64x v0.0.0-20221115062448-fe3a3abad311/go.mod h1:b583jCggY9gE99b6G5LEC39OIiVsWj+R97kbl5odCEk=
+github.com/chewxy/hm v1.0.0 h1:zy/TSv3LV2nD3dwUEQL2VhXeoXbb9QkpmdRAVUFiA6k=
+github.com/chewxy/hm v1.0.0/go.mod h1:qg9YI4q6Fkj/whwHR1D+bOGeF7SniIP40VweVepLjg0=
+github.com/chewxy/math32 v1.0.0/go.mod h1:Miac6hA1ohdDUTagnvJy/q+aNnEk16qWUdb8ZVhvCN0=
+github.com/chewxy/math32 v1.0.8 h1:fU5E4Ec4Z+5RtRAi3TovSxUjQPkgRh+HbP7tKB2OFbM=
+github.com/chewxy/math32 v1.0.8/go.mod h1:dOB2rcuFrCn6UHrze36WSLVPKtzPMRAQvBvUwkSsLqs=
+github.com/client9/misspell v0.3.4/go.mod h1:qj6jICC3Q7zFZvVWo7KLAzC3yx5G7kyvSDkc90ppPyw=
+github.com/cncf/udpa/go v0.0.0-20191209042840-269d4d468f6f/go.mod h1:M8M6+tZqaGXZJjfX53e64911xZQV5JYwmTeXPW+k8Sc=
 github.com/containerd/console v1.0.3 h1:lIr7SlA5PxZyMV30bDW0MGbiOPXwc63yRuCP0ARubLw=
 github.com/containerd/console v1.0.3/go.mod h1:7LqA/THxQ86k76b8c/EMSiaJ3h1eZkMkXar0TQ1gf3U=
 github.com/cpuguy83/go-md2man/v2 v2.0.2/go.mod h1:tgQtvFlXSQOSOSIRvRPT7W67SCa46tRHOmNcaadrF8o=
-github.com/cratonica/2goarray v0.0.0-20190331194516-514510793eaa h1:Wg+722vs7a2zQH5lR9QWYsVbplKeffaQFIs5FTdfNNo=
-github.com/cratonica/2goarray v0.0.0-20190331194516-514510793eaa/go.mod h1:6Arca19mRx58CA7OWEd7Wu1NpC1rd3uDnNs6s1pj/DI=
 github.com/creack/pty v1.1.9/go.mod h1:oKZEueFk5CKHvIhNR5MUki03XCEU+Q6VDXinZuGJ33E=
+github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1 h1:cBzrdJPAFBsgCrDPnZxlp1dF2+k4r1kVpD7+1S1PVjY=
+github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1/go.mod h1:uw2gLcxEuYUlAd/EXyjc/v55nd3+47YAgWbSXVxPrNI=
 github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
 github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
 github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
 github.com/emirpasic/gods v1.18.1 h1:FXtiHYKDGKCW2KzwZKx0iC0PQmdlorYgdFG9jPXJ1Bc=
 github.com/emirpasic/gods v1.18.1/go.mod h1:8tpGGwCnJ5H4r6BWwaV6OrWmMoPhUl5jm/FMNAnJvWQ=
+github.com/envoyproxy/go-control-plane v0.9.0/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=
+github.com/envoyproxy/go-control-plane v0.9.1-0.20191026205805-5f8ba28d4473/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=
+github.com/envoyproxy/go-control-plane v0.9.4/go.mod h1:6rpuAdCZL397s3pYoYcLgu1mIlRU8Am5FuJP05cCM98=
+github.com/envoyproxy/protoc-gen-validate v0.1.0/go.mod h1:iSmxcyjqTsJpI2R4NaDN7+kN2VEUnK/pcBlmesArF7c=
+github.com/fogleman/gg v1.2.1-0.20190220221249-0403632d5b90/go.mod h1:R/bRT+9gY/C5z7JzPU0zXsXHKM4/ayA+zqcVNZzPa1k=
 github.com/gabriel-vasile/mimetype v1.4.2 h1:w5qFW6JKBz9Y393Y4q372O9A7cUSequkh1Q7OhCmWKU=
 github.com/gabriel-vasile/mimetype v1.4.2/go.mod h1:zApsH/mKG4w07erKIaJPFiX0Tsq9BFQgN3qGY5GnNgA=
-github.com/getlantern/context v0.0.0-20190109183933-c447772a6520 h1:NRUJuo3v3WGC/g5YiyF790gut6oQr5f3FBI88Wv0dx4=
-github.com/getlantern/context v0.0.0-20190109183933-c447772a6520/go.mod h1:L+mq6/vvYHKjCX2oez0CgEAJmbq1fbb/oNJIWQkBybY=
-github.com/getlantern/errors v0.0.0-20190325191628-abdb3e3e36f7 h1:6uJ+sZ/e03gkbqZ0kUG6mfKoqDb4XMAzMIwlajq19So=
-github.com/getlantern/errors v0.0.0-20190325191628-abdb3e3e36f7/go.mod h1:l+xpFBrCtDLpK9qNjxs+cHU6+BAdlBaxHqikB6Lku3A=
-github.com/getlantern/golog v0.0.0-20190830074920-4ef2e798c2d7 h1:guBYzEaLz0Vfc/jv0czrr2z7qyzTOGC9hiQ0VC+hKjk=
-github.com/getlantern/golog v0.0.0-20190830074920-4ef2e798c2d7/go.mod h1:zx/1xUUeYPy3Pcmet8OSXLbF47l+3y6hIPpyLWoR9oc=
-github.com/getlantern/hex v0.0.0-20190417191902-c6586a6fe0b7 h1:micT5vkcr9tOVk1FiH8SWKID8ultN44Z+yzd2y/Vyb0=
-github.com/getlantern/hex v0.0.0-20190417191902-c6586a6fe0b7/go.mod h1:dD3CgOrwlzca8ed61CsZouQS5h5jIzkK9ZWrTcf0s+o=
-github.com/getlantern/hidden v0.0.0-20190325191715-f02dbb02be55 h1:XYzSdCbkzOC0FDNrgJqGRo8PCMFOBFL9py72DRs7bmc=
-github.com/getlantern/hidden v0.0.0-20190325191715-f02dbb02be55/go.mod h1:6mmzY2kW1TOOrVy+r41Za2MxXM+hhqTtY3oBKd2AgFA=
-github.com/getlantern/ops v0.0.0-20190325191751-d70cb0d6f85f h1:wrYrQttPS8FHIRSlsrcuKazukx/xqO/PpLZzZXsF+EA=
-github.com/getlantern/ops v0.0.0-20190325191751-d70cb0d6f85f/go.mod h1:D5ao98qkA6pxftxoqzibIBBrLSUli+kYnJqrgBf9cIA=
-github.com/getlantern/systray v1.2.2 h1:dCEHtfmvkJG7HZ8lS/sLklTH4RKUcIsKrAD9sThoEBE=
-github.com/getlantern/systray v1.2.2/go.mod h1:pXFOI1wwqwYXEhLPm9ZGjS2u/vVELeIgNMY5HvhHhcE=
 github.com/gin-contrib/cors v1.4.0 h1:oJ6gwtUl3lqV0WEIwM/LxPF1QZ5qe2lGWdY2+bz7y0g=
 github.com/gin-contrib/cors v1.4.0/go.mod h1:bs9pNM0x/UsmHPBWT2xZz9ROh8xYjYkiURUfmBoMlcs=
 github.com/gin-contrib/sse v0.1.0 h1:Y/yl/+YNO8GZSjAhjMsSuLt29uWRFHdHYUb5lYOV9qE=
@@ -40,6 +44,7 @@ github.com/gin-gonic/gin v1.9.1 h1:4idEAncQnU5cB7BeOkPtxjfCSye0AAm1R0RVIqJ+Jmg=
 github.com/gin-gonic/gin v1.9.1/go.mod h1:hPrL7YrpYKXt5YId3A/Tnip5kqbEAP+KLuI3SUcPTeU=
 github.com/go-playground/assert/v2 v2.0.1/go.mod h1:VDjEfimB/XKnb+ZQfWdccd7VUvScMdVu0Titje2rxJ4=
 github.com/go-playground/assert/v2 v2.2.0 h1:JvknZsQTYeFEAhQwI4qEt9cyV5ONwRHC+lYKSsYSR8s=
+github.com/go-playground/assert/v2 v2.2.0/go.mod h1:VDjEfimB/XKnb+ZQfWdccd7VUvScMdVu0Titje2rxJ4=
 github.com/go-playground/locales v0.14.0/go.mod h1:sawfccIbzZTqEDETgFXqTho0QybSa7l++s0DH+LDiLs=
 github.com/go-playground/locales v0.14.1 h1:EWaQ/wswjilfKLTECiXz7Rh+3BjFhfDFKv/oXslEjJA=
 github.com/go-playground/locales v0.14.1/go.mod h1:hxrqLVvrK65+Rwrd5Fc6F2O76J/NuW9t0sjnWqG1slY=
@@ -49,12 +54,34 @@ github.com/go-playground/universal-translator v0.18.1/go.mod h1:xekY+UJKNuX9WP91
 github.com/go-playground/validator/v10 v10.10.0/go.mod h1:74x4gJWsvQexRdW8Pn3dXSGrTK4nAUsbPlLADvpJkos=
 github.com/go-playground/validator/v10 v10.14.0 h1:vgvQWe3XCz3gIeFDm/HnTIbj6UGmg/+t63MyGU2n5js=
 github.com/go-playground/validator/v10 v10.14.0/go.mod h1:9iXMNT7sEkjXb0I+enO7QXmzG6QCsPWY4zveKFVRSyU=
-github.com/go-stack/stack v1.8.0 h1:5SgMzNM5HxrEjV0ww2lTmX6E2Izsfxas4+YHWRs3Lsk=
-github.com/go-stack/stack v1.8.0/go.mod h1:v0f6uXyyMGvRgIKkXu+yp6POWl0qKG85gN/melR3HDY=
 github.com/goccy/go-json v0.9.7/go.mod h1:6MelG93GURQebXPDq3khkgXZkazVtN9CRI+MGFi0w8I=
 github.com/goccy/go-json v0.10.2 h1:CrxCmQqYDkv1z7lO7Wbh2HN93uovUHgrECaO5ZrCXAU=
 github.com/goccy/go-json v0.10.2/go.mod h1:6MelG93GURQebXPDq3khkgXZkazVtN9CRI+MGFi0w8I=
+github.com/gogo/protobuf v1.3.2 h1:Ov1cvc58UF3b5XjBnZv7+opcTcQFZebYjWzi34vdm4Q=
+github.com/gogo/protobuf v1.3.2/go.mod h1:P1XiOD3dCwIKUDQYPy72D8LYyHL2YPYrpS2s69NZV8Q=
+github.com/golang/freetype v0.0.0-20170609003504-e2365dfdc4a0/go.mod h1:E/TSTwGwJL78qG/PmXZO1EjYhfJinVAhrmmHX6Z8B9k=
+github.com/golang/glog v0.0.0-20160126235308-23def4e6c14b/go.mod h1:SBH7ygxi8pfUlaOkMMuAQtPIUF8ecWP5IEl/CR7VP2Q=
+github.com/golang/mock v1.1.1/go.mod h1:oTYuIxOrZwtPieC+H1uAHpcLFnEyAGVDL/k47Jfbm0A=
+github.com/golang/protobuf v1.2.0/go.mod h1:6lQm79b+lXiMfvg/cZm0SGofjICqVBUtrP5yJMmIC1U=
+github.com/golang/protobuf v1.3.2/go.mod h1:6lQm79b+lXiMfvg/cZm0SGofjICqVBUtrP5yJMmIC1U=
+github.com/golang/protobuf v1.3.3/go.mod h1:vzj43D7+SQXF/4pzW/hwtAqwc6iTitCiVSaWz5lYuqw=
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@@ -65,6 +92,9 @@ github.com/inconshreveable/mousetrap v1.1.0 h1:wN+x4NVGpMsO7ErUn/mUI3vEoE6Jt13X2
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@@ -120,6 +150,8 @@ github.com/spf13/pflag v1.0.5/go.mod h1:McXfInJRrz4CZXVZOBLb0bTZqETkiAhM9Iw0y3An
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@@ -136,44 +168,127 @@ github.com/ugorji/go v1.2.7/go.mod h1:nF9osbDWLy6bDVv/Rtoh6QgnvNDpmCalQV5urGCCS6
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@@ -184,4 +299,10 @@ gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C
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gpu/amd.go

@@ -1,101 +0,0 @@
-package gpu
-
-import (
-	"bufio"
-	"errors"
-	"fmt"
-	"io"
-	"log/slog"
-	"os"
-	"path/filepath"
-	"strconv"
-	"strings"
-)
-
-// TODO - windows vs. non-windows vs darwin
-
-// Discovery logic for AMD/ROCm GPUs
-
-const (
-	DriverVersionFile     = "/sys/module/amdgpu/version"
-	GPUPropertiesFileGlob = "/sys/class/kfd/kfd/topology/nodes/*/properties"
-	// TODO probably break these down per GPU to make the logic simpler
-	GPUTotalMemoryFileGlob = "/sys/class/kfd/kfd/topology/nodes/*/mem_banks/*/properties" // size_in_bytes line
-	GPUUsedMemoryFileGlob  = "/sys/class/kfd/kfd/topology/nodes/*/mem_banks/*/used_memory"
-)
-
-func AMDDetected() bool {
-	// Some driver versions (older?) don't have a version file, so just lookup the parent dir
-	sysfsDir := filepath.Dir(DriverVersionFile)
-	_, err := os.Stat(sysfsDir)
-	if errors.Is(err, os.ErrNotExist) {
-		slog.Debug("amd driver not detected " + sysfsDir)
-		return false
-	} else if err != nil {
-		slog.Debug(fmt.Sprintf("error looking up amd driver %s %s", sysfsDir, err))
-		return false
-	}
-	return true
-}
-
-func AMDDriverVersion() (string, error) {
-	_, err := os.Stat(DriverVersionFile)
-	if err != nil {
-		return "", fmt.Errorf("amdgpu file stat error: %s %w", DriverVersionFile, err)
-	}
-	fp, err := os.Open(DriverVersionFile)
-	if err != nil {
-		return "", err
-	}
-	defer fp.Close()
-	verString, err := io.ReadAll(fp)
-	if err != nil {
-		return "", err
-	}
-	return strings.TrimSpace(string(verString)), nil
-}
-
-func AMDGFXVersions() []Version {
-	res := []Version{}
-	matches, _ := filepath.Glob(GPUPropertiesFileGlob)
-	for _, match := range matches {
-		fp, err := os.Open(match)
-		if err != nil {
-			slog.Debug(fmt.Sprintf("failed to open sysfs node file %s: %s", match, err))
-			continue
-		}
-		defer fp.Close()
-
-		scanner := bufio.NewScanner(fp)
-		// optionally, resize scanner's capacity for lines over 64K, see next example
-		for scanner.Scan() {
-			line := strings.TrimSpace(scanner.Text())
-			if strings.HasPrefix(line, "gfx_target_version") {
-				ver := strings.Fields(line)
-				if len(ver) != 2 || len(ver[1]) < 5 {
-					slog.Debug("malformed " + line)
-					continue
-				}
-				l := len(ver[1])
-				patch, err1 := strconv.ParseUint(ver[1][l-2:l], 10, 32)
-				minor, err2 := strconv.ParseUint(ver[1][l-4:l-2], 10, 32)
-				major, err3 := strconv.ParseUint(ver[1][:l-4], 10, 32)
-				if err1 != nil || err2 != nil || err3 != nil {
-					slog.Debug("malformed int " + line)
-					continue
-				}
-
-				res = append(res, Version{
-					Major: uint(major),
-					Minor: uint(minor),
-					Patch: uint(patch),
-				})
-			}
-		}
-	}
-	return res
-}
-
-func (v Version) ToGFXString() string {
-	return fmt.Sprintf("gfx%d%d%d", v.Major, v.Minor, v.Patch)
-}

gpu/amd_common.go

@@ -0,0 +1,98 @@
+//go:build linux || windows
+
+package gpu
+
+import (
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"runtime"
+	"strings"
+)
+
+// Determine if the given ROCm lib directory is usable by checking for existence of some glob patterns
+func rocmLibUsable(libDir string) bool {
+	slog.Debug("evaluating potential rocm lib dir " + libDir)
+	for _, g := range ROCmLibGlobs {
+		res, _ := filepath.Glob(filepath.Join(libDir, g))
+		if len(res) == 0 {
+			return false
+		}
+	}
+	return true
+}
+
+func GetSupportedGFX(libDir string) ([]string, error) {
+	var ret []string
+	files, err := filepath.Glob(filepath.Join(libDir, "rocblas", "library", "TensileLibrary_lazy_gfx*.dat"))
+	if err != nil {
+		return nil, err
+	}
+	for _, file := range files {
+		ret = append(ret, strings.TrimSuffix(strings.TrimPrefix(filepath.Base(file), "TensileLibrary_lazy_"), ".dat"))
+	}
+	return ret, nil
+}
+
+func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
+	ids := []string{}
+	for _, info := range gpuInfo {
+		if info.Library != "rocm" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("rocmGetVisibleDevicesEnv skipping over non-rocm device", "library", info.Library)
+			continue
+		}
+		ids = append(ids, info.ID)
+	}
+	return "HIP_VISIBLE_DEVICES", strings.Join(ids, ",")
+}
+
+func commonAMDValidateLibDir() (string, error) {
+	// We try to favor system paths first, so that we can wire up the subprocess to use
+	// the system version.  Only use our bundled version if the system version doesn't work
+	// This gives users a more recovery options if versions have subtle problems at runtime
+
+	// Prefer explicit HIP env var
+	hipPath := os.Getenv("HIP_PATH")
+	if hipPath != "" {
+		hipLibDir := filepath.Join(hipPath, "bin")
+		if rocmLibUsable(hipLibDir) {
+			slog.Debug("detected ROCM via HIP_PATH=" + hipPath)
+			return hipLibDir, nil
+		}
+	}
+
+	// Scan the LD_LIBRARY_PATH or PATH
+	pathEnv := "LD_LIBRARY_PATH"
+	if runtime.GOOS == "windows" {
+		pathEnv = "PATH"
+	}
+
+	paths := os.Getenv(pathEnv)
+	for _, path := range filepath.SplitList(paths) {
+		d, err := filepath.Abs(path)
+		if err != nil {
+			continue
+		}
+		if rocmLibUsable(d) {
+			return d, nil
+		}
+	}
+
+	// Well known location(s)
+	if rocmLibUsable(RocmStandardLocation) {
+		return RocmStandardLocation, nil
+	}
+
+	// Installer payload location if we're running the installed binary
+	exe, err := os.Executable()
+	if err == nil {
+		rocmTargetDir := filepath.Join(filepath.Dir(exe), "rocm")
+		if rocmLibUsable(rocmTargetDir) {
+			slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
+			return rocmTargetDir, nil
+		}
+	}
+	return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
+}

gpu/amd_hip_windows.go

@@ -0,0 +1,141 @@
+package gpu
+
+import (
+	"fmt"
+	"log/slog"
+	"strconv"
+	"syscall"
+	"unsafe"
+
+	"golang.org/x/sys/windows"
+)
+
+const (
+	hipSuccess       = 0
+	hipErrorNoDevice = 100
+)
+
+type hipDevicePropMinimal struct {
+	Name        [256]byte
+	unused1     [140]byte
+	GcnArchName [256]byte // gfx####
+	iGPU        int       // Doesn't seem to actually report correctly
+	unused2     [128]byte
+}
+
+// Wrap the amdhip64.dll library for GPU discovery
+type HipLib struct {
+	dll                    windows.Handle
+	hipGetDeviceCount      uintptr
+	hipGetDeviceProperties uintptr
+	hipMemGetInfo          uintptr
+	hipSetDevice           uintptr
+	hipDriverGetVersion    uintptr
+}
+
+func NewHipLib() (*HipLib, error) {
+	h, err := windows.LoadLibrary("amdhip64.dll")
+	if err != nil {
+		return nil, fmt.Errorf("unable to load amdhip64.dll: %w", err)
+	}
+	hl := &HipLib{}
+	hl.dll = h
+	hl.hipGetDeviceCount, err = windows.GetProcAddress(hl.dll, "hipGetDeviceCount")
+	if err != nil {
+		return nil, err
+	}
+	hl.hipGetDeviceProperties, err = windows.GetProcAddress(hl.dll, "hipGetDeviceProperties")
+	if err != nil {
+		return nil, err
+	}
+	hl.hipMemGetInfo, err = windows.GetProcAddress(hl.dll, "hipMemGetInfo")
+	if err != nil {
+		return nil, err
+	}
+	hl.hipSetDevice, err = windows.GetProcAddress(hl.dll, "hipSetDevice")
+	if err != nil {
+		return nil, err
+	}
+	hl.hipDriverGetVersion, err = windows.GetProcAddress(hl.dll, "hipDriverGetVersion")
+	if err != nil {
+		return nil, err
+	}
+	return hl, nil
+}
+
+// The hip library only evaluates the HIP_VISIBLE_DEVICES variable at startup
+// so we have to unload/reset the library after we do our initial discovery
+// to make sure our updates to that variable are processed by llama.cpp
+func (hl *HipLib) Release() {
+	err := windows.FreeLibrary(hl.dll)
+	if err != nil {
+		slog.Warn("failed to unload amdhip64.dll", "error", err)
+	}
+	hl.dll = 0
+}
+
+func (hl *HipLib) AMDDriverVersion() (string, error) {
+	if hl.dll == 0 {
+		return "", fmt.Errorf("dll has been unloaded")
+	}
+	var version int
+	status, _, err := syscall.SyscallN(hl.hipDriverGetVersion, uintptr(unsafe.Pointer(&version)))
+	if status != hipSuccess {
+		return "", fmt.Errorf("failed call to hipDriverGetVersion: %d %s", status, err)
+	}
+	return strconv.Itoa(version), nil
+}
+
+func (hl *HipLib) HipGetDeviceCount() int {
+	if hl.dll == 0 {
+		slog.Error("dll has been unloaded")
+		return 0
+	}
+	var count int
+	status, _, err := syscall.SyscallN(hl.hipGetDeviceCount, uintptr(unsafe.Pointer(&count)))
+	if status == hipErrorNoDevice {
+		slog.Info("AMD ROCm reports no devices found")
+		return 0
+	}
+	if status != hipSuccess {
+		slog.Warn("failed call to hipGetDeviceCount", "status", status, "error", err)
+	}
+	return count
+}
+
+func (hl *HipLib) HipSetDevice(device int) error {
+	if hl.dll == 0 {
+		return fmt.Errorf("dll has been unloaded")
+	}
+	status, _, err := syscall.SyscallN(hl.hipSetDevice, uintptr(device))
+	if status != hipSuccess {
+		return fmt.Errorf("failed call to hipSetDevice: %d %s", status, err)
+	}
+	return nil
+}
+
+func (hl *HipLib) HipGetDeviceProperties(device int) (*hipDevicePropMinimal, error) {
+	if hl.dll == 0 {
+		return nil, fmt.Errorf("dll has been unloaded")
+	}
+	var props hipDevicePropMinimal
+	status, _, err := syscall.SyscallN(hl.hipGetDeviceProperties, uintptr(unsafe.Pointer(&props)), uintptr(device))
+	if status != hipSuccess {
+		return nil, fmt.Errorf("failed call to hipGetDeviceProperties: %d %s", status, err)
+	}
+	return &props, nil
+}
+
+// free, total, err
+func (hl *HipLib) HipMemGetInfo() (uint64, uint64, error) {
+	if hl.dll == 0 {
+		return 0, 0, fmt.Errorf("dll has been unloaded")
+	}
+	var totalMemory uint64
+	var freeMemory uint64
+	status, _, err := syscall.SyscallN(hl.hipMemGetInfo, uintptr(unsafe.Pointer(&freeMemory)), uintptr(unsafe.Pointer(&totalMemory)))
+	if status != hipSuccess {
+		return 0, 0, fmt.Errorf("failed call to hipMemGetInfo: %d %s", status, err)
+	}
+	return freeMemory, totalMemory, nil
+}

gpu/amd_linux.go

@@ -0,0 +1,340 @@
+package gpu
+
+import (
+	"bufio"
+	"errors"
+	"fmt"
+	"io"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"slices"
+	"strconv"
+	"strings"
+
+	"github.com/ollama/ollama/format"
+)
+
+// Discovery logic for AMD/ROCm GPUs
+
+const (
+	DriverVersionFile     = "/sys/module/amdgpu/version"
+	AMDNodesSysfsDir      = "/sys/class/kfd/kfd/topology/nodes/"
+	GPUPropertiesFileGlob = AMDNodesSysfsDir + "*/properties"
+
+	// Prefix with the node dir
+	GPUTotalMemoryFileGlob = "mem_banks/*/properties" // size_in_bytes line
+	GPUUsedMemoryFileGlob  = "mem_banks/*/used_memory"
+	RocmStandardLocation   = "/opt/rocm/lib"
+)
+
+var (
+	// Used to validate if the given ROCm lib is usable
+	ROCmLibGlobs = []string{"libhipblas.so.2*", "rocblas"} // TODO - probably include more coverage of files here...
+)
+
+// Gather GPU information from the amdgpu driver if any supported GPUs are detected
+func AMDGetGPUInfo() []GpuInfo {
+	resp := []GpuInfo{}
+	if !AMDDetected() {
+		return resp
+	}
+
+	// Opportunistic logging of driver version to aid in troubleshooting
+	ver, err := AMDDriverVersion()
+	if err == nil {
+		slog.Info("AMD Driver: " + ver)
+	} else {
+		// TODO - if we see users crash and burn with the upstreamed kernel this can be adjusted to hard-fail rocm support and fallback to CPU
+		slog.Warn("ollama recommends running the https://www.amd.com/en/support/linux-drivers", "error", err)
+	}
+
+	// Determine if the user has already pre-selected which GPUs to look at, then ignore the others
+	var visibleDevices []string
+	hipVD := os.Getenv("HIP_VISIBLE_DEVICES")   // zero based index only
+	rocrVD := os.Getenv("ROCR_VISIBLE_DEVICES") // zero based index or UUID, but consumer cards seem to not support UUID
+	gpuDO := os.Getenv("GPU_DEVICE_ORDINAL")    // zero based index
+	switch {
+	// TODO is this priorty order right?
+	case hipVD != "":
+		visibleDevices = strings.Split(hipVD, ",")
+	case rocrVD != "":
+		visibleDevices = strings.Split(rocrVD, ",")
+		// TODO - since we don't yet support UUIDs, consider detecting and reporting here
+		// all our test systems show GPU-XX indicating UUID is not supported
+	case gpuDO != "":
+		visibleDevices = strings.Split(gpuDO, ",")
+	}
+
+	gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
+	var supported []string
+	libDir := ""
+
+	// The amdgpu driver always exposes the host CPU(s) first, but we have to skip them and subtract
+	// from the other IDs to get alignment with the HIP libraries expectations (zero is the first GPU, not the CPU)
+	matches, _ := filepath.Glob(GPUPropertiesFileGlob)
+	cpuCount := 0
+	for _, match := range matches {
+		slog.Debug("evaluating amdgpu node " + match)
+		fp, err := os.Open(match)
+		if err != nil {
+			slog.Debug("failed to open sysfs node", "file", match, "error", err)
+			continue
+		}
+		defer fp.Close()
+		nodeID, err := strconv.Atoi(filepath.Base(filepath.Dir(match)))
+		if err != nil {
+			slog.Debug("failed to parse node ID", "error", err)
+			continue
+		}
+
+		scanner := bufio.NewScanner(fp)
+		isCPU := false
+		var major, minor, patch uint64
+		for scanner.Scan() {
+			line := strings.TrimSpace(scanner.Text())
+			// Note: we could also use "cpu_cores_count X" where X is greater than zero to detect CPUs
+			if strings.HasPrefix(line, "gfx_target_version") {
+				ver := strings.Fields(line)
+
+				// Detect CPUs
+				if len(ver) == 2 && ver[1] == "0" {
+					slog.Debug("detected CPU " + match)
+					isCPU = true
+					break
+				}
+
+				if len(ver) != 2 || len(ver[1]) < 5 {
+					slog.Warn("malformed "+match, "gfx_target_version", line)
+					// If this winds up being a CPU, our offsets may be wrong
+					continue
+				}
+				l := len(ver[1])
+				var err1, err2, err3 error
+				patch, err1 = strconv.ParseUint(ver[1][l-2:l], 10, 32)
+				minor, err2 = strconv.ParseUint(ver[1][l-4:l-2], 10, 32)
+				major, err3 = strconv.ParseUint(ver[1][:l-4], 10, 32)
+				if err1 != nil || err2 != nil || err3 != nil {
+					slog.Debug("malformed int " + line)
+					continue
+				}
+			}
+
+			// TODO - any other properties we want to extract and record?
+			// vendor_id + device_id -> pci lookup for "Name"
+			// Other metrics that may help us understand relative performance between multiple GPUs
+		}
+
+		if isCPU {
+			cpuCount++
+			continue
+		}
+
+		// CPUs are always first in the list
+		gpuID := nodeID - cpuCount
+
+		// Shouldn't happen, but just in case...
+		if gpuID < 0 {
+			slog.Error("unexpected amdgpu sysfs data resulted in negative GPU ID, please set OLLAMA_DEBUG=1 and report an issue")
+			return []GpuInfo{}
+		}
+
+		if int(major) < RocmComputeMin {
+			slog.Warn(fmt.Sprintf("amdgpu too old gfx%d%d%x", major, minor, patch), "gpu", gpuID)
+			continue
+		}
+
+		// Look up the memory for the current node
+		totalMemory := uint64(0)
+		usedMemory := uint64(0)
+		propGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUTotalMemoryFileGlob)
+		propFiles, err := filepath.Glob(propGlob)
+		if err != nil {
+			slog.Warn("error looking up total GPU memory", "glob", propGlob, "error", err)
+		}
+		// 1 or more memory banks - sum the values of all of them
+		for _, propFile := range propFiles {
+			fp, err := os.Open(propFile)
+			if err != nil {
+				slog.Warn("failed to open sysfs node", "file", propFile, "erroir", err)
+				continue
+			}
+			defer fp.Close()
+			scanner := bufio.NewScanner(fp)
+			for scanner.Scan() {
+				line := strings.TrimSpace(scanner.Text())
+				if strings.HasPrefix(line, "size_in_bytes") {
+					ver := strings.Fields(line)
+					if len(ver) != 2 {
+						slog.Warn("malformed " + line)
+						continue
+					}
+					bankSizeInBytes, err := strconv.ParseUint(ver[1], 10, 64)
+					if err != nil {
+						slog.Warn("malformed int " + line)
+						continue
+					}
+					totalMemory += bankSizeInBytes
+				}
+			}
+		}
+		if totalMemory == 0 {
+			slog.Warn("amdgpu reports zero total memory", "gpu", gpuID)
+			continue
+		}
+		usedGlob := filepath.Join(AMDNodesSysfsDir, strconv.Itoa(nodeID), GPUUsedMemoryFileGlob)
+		usedFiles, err := filepath.Glob(usedGlob)
+		if err != nil {
+			slog.Warn("error looking up used GPU memory", "glob", usedGlob, "error", err)
+			continue
+		}
+		for _, usedFile := range usedFiles {
+			fp, err := os.Open(usedFile)
+			if err != nil {
+				slog.Warn("failed to open sysfs node", "file", usedFile, "error", err)
+				continue
+			}
+			defer fp.Close()
+			data, err := io.ReadAll(fp)
+			if err != nil {
+				slog.Warn("failed to read sysfs node", "file", usedFile, "error", err)
+				continue
+			}
+			used, err := strconv.ParseUint(strings.TrimSpace(string(data)), 10, 64)
+			if err != nil {
+				slog.Warn("malformed used memory", "data", string(data), "error", err)
+				continue
+			}
+			usedMemory += used
+		}
+
+		// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
+		if totalMemory < IGPUMemLimit {
+			slog.Info("amdgpu appears to be an iGPU, skipping", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
+			continue
+		}
+
+		slog.Info("amdgpu memory", "gpu", gpuID, "total", format.HumanBytes2(totalMemory))
+		slog.Info("amdgpu memory", "gpu", gpuID, "available", format.HumanBytes2(totalMemory-usedMemory))
+		gpuInfo := GpuInfo{
+			Library: "rocm",
+			memInfo: memInfo{
+				TotalMemory: totalMemory,
+				FreeMemory:  (totalMemory - usedMemory),
+			},
+			ID: fmt.Sprintf("%d", gpuID),
+			// Name: not exposed in sysfs directly, would require pci device id lookup
+			Major:         int(major),
+			Minor:         int(minor),
+			Patch:         int(patch),
+			MinimumMemory: rocmMinimumMemory,
+		}
+
+		// If the user wants to filter to a subset of devices, filter out if we aren't a match
+		if len(visibleDevices) > 0 {
+			include := false
+			for _, visible := range visibleDevices {
+				if visible == gpuInfo.ID {
+					include = true
+					break
+				}
+			}
+			if !include {
+				slog.Info("filtering out device per user request", "id", gpuInfo.ID, "visible_devices", visibleDevices)
+				continue
+			}
+		}
+
+		// Final validation is gfx compatibility - load the library if we haven't already loaded it
+		// even if the user overrides, we still need to validate the library
+		if libDir == "" {
+			libDir, err = AMDValidateLibDir()
+			if err != nil {
+				slog.Warn("unable to verify rocm library, will use cpu", "error", err)
+				return []GpuInfo{}
+			}
+		}
+		gpuInfo.DependencyPath = libDir
+
+		if gfxOverride == "" {
+			// Only load supported list once
+			if len(supported) == 0 {
+				supported, err = GetSupportedGFX(libDir)
+				if err != nil {
+					slog.Warn("failed to lookup supported GFX types, falling back to CPU mode", "error", err)
+					return []GpuInfo{}
+				}
+				slog.Debug("rocm supported GPUs", "types", supported)
+			}
+			gfx := fmt.Sprintf("gfx%d%d%x", gpuInfo.Major, gpuInfo.Minor, gpuInfo.Patch)
+			if !slices.Contains[[]string, string](supported, gfx) {
+				slog.Warn("amdgpu is not supported", "gpu", gpuInfo.ID, "gpu_type", gfx, "library", libDir, "supported_types", supported)
+				// TODO - consider discrete markdown just for ROCM troubleshooting?
+				slog.Warn("See https://github.com/ollama/ollama/blob/main/docs/gpu.md#overrides for HSA_OVERRIDE_GFX_VERSION usage")
+				continue
+			} else {
+				slog.Info("amdgpu is supported", "gpu", gpuInfo.ID, "gpu_type", gfx)
+			}
+		} else {
+			slog.Debug("skipping rocm gfx compatibility check with HSA_OVERRIDE_GFX_VERSION=" + gfxOverride)
+		}
+
+		// The GPU has passed all the verification steps and is supported
+		resp = append(resp, gpuInfo)
+	}
+	if len(resp) == 0 {
+		slog.Info("no compatible amdgpu devices detected")
+	}
+	return resp
+}
+
+// Quick check for AMD driver so we can skip amdgpu discovery if not present
+func AMDDetected() bool {
+	// Some driver versions (older?) don't have a version file, so just lookup the parent dir
+	sysfsDir := filepath.Dir(DriverVersionFile)
+	_, err := os.Stat(sysfsDir)
+	if errors.Is(err, os.ErrNotExist) {
+		slog.Debug("amdgpu driver not detected " + sysfsDir)
+		return false
+	} else if err != nil {
+		slog.Debug("error looking up amd driver", "path", sysfsDir, "error", err)
+		return false
+	}
+	return true
+}
+
+// Prefer to use host installed ROCm, as long as it meets our minimum requirements
+// failing that, tell the user how to download it on their own
+func AMDValidateLibDir() (string, error) {
+	libDir, err := commonAMDValidateLibDir()
+	if err == nil {
+		return libDir, nil
+	}
+
+	// Well known ollama installer path
+	installedRocmDir := "/usr/share/ollama/lib/rocm"
+	if rocmLibUsable(installedRocmDir) {
+		return installedRocmDir, nil
+	}
+
+	// If we still haven't found a usable rocm, the user will have to install it on their own
+	slog.Warn("amdgpu detected, but no compatible rocm library found.  Either install rocm v6, or follow manual install instructions at https://github.com/ollama/ollama/blob/main/docs/linux.md#manual-install")
+	return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
+}
+
+func AMDDriverVersion() (string, error) {
+	_, err := os.Stat(DriverVersionFile)
+	if err != nil {
+		return "", fmt.Errorf("amdgpu version file missing: %s %w", DriverVersionFile, err)
+	}
+	fp, err := os.Open(DriverVersionFile)
+	if err != nil {
+		return "", err
+	}
+	defer fp.Close()
+	verString, err := io.ReadAll(fp)
+	if err != nil {
+		return "", err
+	}
+	return strings.TrimSpace(string(verString)), nil
+}

gpu/amd_windows.go

@@ -0,0 +1,189 @@
+package gpu
+
+import (
+	"bytes"
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"slices"
+	"strconv"
+	"strings"
+
+	"github.com/ollama/ollama/format"
+)
+
+const (
+	RocmStandardLocation = "C:\\Program Files\\AMD\\ROCm\\5.7\\bin" // TODO glob?
+
+	// TODO  We're lookinng for this exact name to detect iGPUs since hipGetDeviceProperties never reports integrated==true
+	iGPUName = "AMD Radeon(TM) Graphics"
+)
+
+var (
+	// Used to validate if the given ROCm lib is usable
+	ROCmLibGlobs = []string{"hipblas.dll", "rocblas"} // TODO - probably include more coverage of files here...
+)
+
+func AMDGetGPUInfo() []GpuInfo {
+	resp := []GpuInfo{}
+	hl, err := NewHipLib()
+	if err != nil {
+		slog.Debug(err.Error())
+		return nil
+	}
+	defer hl.Release()
+
+	ver, err := hl.AMDDriverVersion()
+	if err == nil {
+		slog.Info("AMD Driver: " + ver)
+	} else {
+		// For now this is benign, but we may eventually need to fail compatibility checks
+		slog.Debug("error looking up amd driver version", "error", err)
+	}
+
+	// Note: the HIP library automatically handles subsetting to any HIP_VISIBLE_DEVICES the user specified
+	count := hl.HipGetDeviceCount()
+	if count == 0 {
+		return nil
+	}
+	libDir, err := AMDValidateLibDir()
+	if err != nil {
+		slog.Warn("unable to verify rocm library, will use cpu", "error", err)
+		return nil
+	}
+
+	var supported []string
+	gfxOverride := os.Getenv("HSA_OVERRIDE_GFX_VERSION")
+	if gfxOverride == "" {
+		supported, err = GetSupportedGFX(libDir)
+		if err != nil {
+			slog.Warn("failed to lookup supported GFX types, falling back to CPU mode", "error", err)
+			return nil
+		}
+	} else {
+		slog.Debug("skipping rocm gfx compatibility check with HSA_OVERRIDE_GFX_VERSION=" + gfxOverride)
+	}
+
+	slog.Info("detected hip devices", "count", count)
+	// TODO how to determine the underlying device ID when visible devices is causing this to subset?
+	for i := 0; i < count; i++ {
+		err = hl.HipSetDevice(i)
+		if err != nil {
+			slog.Warn("set device", "id", i, "error", err)
+			continue
+		}
+
+		props, err := hl.HipGetDeviceProperties(i)
+		if err != nil {
+			slog.Warn("get properties", "id", i, "error", err)
+			continue
+		}
+		n := bytes.IndexByte(props.Name[:], 0)
+		name := string(props.Name[:n])
+		// TODO is UUID actually populated on windows?
+		// Can luid be used on windows for setting visible devices (and is it actually set?)
+		n = bytes.IndexByte(props.GcnArchName[:], 0)
+		gfx := string(props.GcnArchName[:n])
+		slog.Info("hip device", "id", i, "name", name, "gfx", gfx)
+		var major, minor, patch string
+		switch len(gfx) {
+		case 6:
+			major, minor, patch = gfx[3:4], gfx[4:5], gfx[5:]
+		case 7:
+			major, minor, patch = gfx[3:5], gfx[5:6], gfx[6:]
+		}
+		//slog.Info(fmt.Sprintf("[%d] Integrated: %d", i, props.iGPU)) // DOESN'T REPORT CORRECTLY!  Always 0
+		// TODO  Why isn't props.iGPU accurate!?
+		if strings.EqualFold(name, iGPUName) {
+			slog.Info("iGPU detected skipping", "id", i)
+			continue
+		}
+		if gfxOverride == "" {
+			if !slices.Contains[[]string, string](supported, gfx) {
+				slog.Warn("amdgpu is not supported", "gpu", i, "gpu_type", gfx, "library", libDir, "supported_types", supported)
+				// TODO - consider discrete markdown just for ROCM troubleshooting?
+				slog.Warn("See https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for HSA_OVERRIDE_GFX_VERSION usage")
+				continue
+			} else {
+				slog.Info("amdgpu is supported", "gpu", i, "gpu_type", gfx)
+			}
+		}
+
+		freeMemory, totalMemory, err := hl.HipMemGetInfo()
+		if err != nil {
+			slog.Warn("get mem info", "id", i, "error", err)
+			continue
+		}
+
+		// iGPU detection, remove this check once we can support an iGPU variant of the rocm library
+		if totalMemory < IGPUMemLimit {
+			slog.Info("amdgpu appears to be an iGPU, skipping", "gpu", i, "total", format.HumanBytes2(totalMemory))
+			continue
+		}
+
+		// TODO revisit this once ROCm v6 is available on windows.
+		// v5.7 only reports VRAM used by this process, so it's completely wrong and unusable
+		slog.Info("amdgpu memory", "gpu", i, "total", format.HumanBytes2(totalMemory))
+		slog.Info("amdgpu memory", "gpu", i, "available", format.HumanBytes2(freeMemory))
+		gpuInfo := GpuInfo{
+			Library: "rocm",
+			memInfo: memInfo{
+				TotalMemory: totalMemory,
+				FreeMemory:  freeMemory,
+			},
+			ID:             fmt.Sprintf("%d", i), // TODO this is probably wrong if we specify visible devices
+			DependencyPath: libDir,
+			MinimumMemory:  rocmMinimumMemory,
+		}
+		if major != "" {
+			gpuInfo.Major, err = strconv.Atoi(major)
+			if err != nil {
+				slog.Info("failed to parse version", "version", gfx, "error", err)
+			}
+		}
+		if minor != "" {
+			gpuInfo.Minor, err = strconv.Atoi(minor)
+			if err != nil {
+				slog.Info("failed to parse version", "version", gfx, "error", err)
+			}
+		}
+		if patch != "" {
+			// Patch rev is hex; e.g. gfx90a
+			p, err := strconv.ParseInt(patch, 16, 0)
+			if err != nil {
+				slog.Info("failed to parse version", "version", gfx, "error", err)
+			} else {
+				gpuInfo.Patch = int(p)
+			}
+		}
+		if gpuInfo.Major < RocmComputeMin {
+			slog.Warn(fmt.Sprintf("amdgpu [%s] too old gfx%d%d%x", gpuInfo.ID, gpuInfo.Major, gpuInfo.Minor, gpuInfo.Patch))
+			continue
+		}
+
+		resp = append(resp, gpuInfo)
+	}
+
+	return resp
+}
+
+func AMDValidateLibDir() (string, error) {
+	libDir, err := commonAMDValidateLibDir()
+	if err == nil {
+		return libDir, nil
+	}
+
+	// Installer payload (if we're running from some other location)
+	localAppData := os.Getenv("LOCALAPPDATA")
+	appDir := filepath.Join(localAppData, "Programs", "Ollama")
+	rocmTargetDir := filepath.Join(appDir, "rocm")
+	if rocmLibUsable(rocmTargetDir) {
+		slog.Debug("detected ollama installed ROCm at " + rocmTargetDir)
+		return rocmTargetDir, nil
+	}
+
+	// Should not happen on windows since we include it in the installer, but stand-alone binary might hit this
+	slog.Warn("amdgpu detected, but no compatible rocm library found.  Please install ROCm")
+	return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
+}

gpu/assets.go

@@ -0,0 +1,157 @@
+package gpu
+
+import (
+	"errors"
+	"fmt"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"runtime"
+	"strconv"
+	"strings"
+	"sync"
+	"syscall"
+	"time"
+)
+
+var (
+	lock        sync.Mutex
+	payloadsDir = ""
+)
+
+func PayloadsDir() (string, error) {
+	lock.Lock()
+	defer lock.Unlock()
+	var err error
+	if payloadsDir == "" {
+		runnersDir := os.Getenv("OLLAMA_RUNNERS_DIR")
+		// On Windows we do not carry the payloads inside the main executable
+		if runtime.GOOS == "windows" && runnersDir == "" {
+			appExe, err := os.Executable()
+			if err != nil {
+				slog.Error("failed to lookup executable path", "error", err)
+				return "", err
+			}
+			// Try a few variations to improve developer experience when building from source in the local tree
+			for _, d := range []string{".", "windows-" + runtime.GOARCH, "dist\\windows-" + runtime.GOARCH} {
+				candidate := filepath.Join(filepath.Dir(appExe), d, "ollama_runners")
+				_, err := os.Stat(candidate)
+				if err == nil {
+					runnersDir = candidate
+					break
+				}
+			}
+			if runnersDir == "" {
+				err = fmt.Errorf("unable to locate llm runner directory.  Set OLLAMA_RUNNERS_DIR to the location of 'ollama_runners'")
+				slog.Error("incomplete distribution", "error", err)
+				return "", err
+			}
+		}
+		if runnersDir != "" {
+			payloadsDir = runnersDir
+			return payloadsDir, nil
+		}
+
+		// The remainder only applies on non-windows where we still carry payloads in the main executable
+		cleanupTmpDirs()
+		tmpDir := os.Getenv("OLLAMA_TMPDIR")
+		if tmpDir == "" {
+			tmpDir, err = os.MkdirTemp("", "ollama")
+			if err != nil {
+				return "", fmt.Errorf("failed to generate tmp dir: %w", err)
+			}
+		} else {
+			err = os.MkdirAll(tmpDir, 0755)
+			if err != nil {
+				return "", fmt.Errorf("failed to generate tmp dir %s: %w", tmpDir, err)
+			}
+		}
+
+		// Track our pid so we can clean up orphaned tmpdirs
+		pidFilePath := filepath.Join(tmpDir, "ollama.pid")
+		pidFile, err := os.OpenFile(pidFilePath, os.O_CREATE|os.O_TRUNC|os.O_WRONLY, os.ModePerm)
+		if err != nil {
+			return "", err
+		}
+		if _, err := pidFile.Write([]byte(fmt.Sprint(os.Getpid()))); err != nil {
+			return "", err
+		}
+
+		// We create a distinct subdirectory for payloads within the tmpdir
+		// This will typically look like /tmp/ollama3208993108/runners on linux
+		payloadsDir = filepath.Join(tmpDir, "runners")
+	}
+	return payloadsDir, nil
+}
+
+// Best effort to clean up prior tmpdirs
+func cleanupTmpDirs() {
+	dirs, err := filepath.Glob(filepath.Join(os.TempDir(), "ollama*"))
+	if err != nil {
+		return
+	}
+	for _, d := range dirs {
+		info, err := os.Stat(d)
+		if err != nil || !info.IsDir() {
+			continue
+		}
+		raw, err := os.ReadFile(filepath.Join(d, "ollama.pid"))
+		if err == nil {
+			pid, err := strconv.Atoi(string(raw))
+			if err == nil {
+				if proc, err := os.FindProcess(int(pid)); err == nil && !errors.Is(proc.Signal(syscall.Signal(0)), os.ErrProcessDone) {
+					// Another running ollama, ignore this tmpdir
+					continue
+				}
+			}
+		} else {
+			slog.Debug("failed to open ollama.pid", "path", d, "error", err)
+		}
+		err = os.RemoveAll(d)
+		if err != nil {
+			slog.Debug("unable to cleanup stale tmpdir", "path", d, "error", err)
+		}
+	}
+}
+
+func Cleanup() {
+	lock.Lock()
+	defer lock.Unlock()
+	runnersDir := os.Getenv("OLLAMA_RUNNERS_DIR")
+	if payloadsDir != "" && runnersDir == "" && runtime.GOOS != "windows" {
+		// We want to fully clean up the tmpdir parent of the payloads dir
+		tmpDir := filepath.Clean(filepath.Join(payloadsDir, ".."))
+		slog.Debug("cleaning up", "dir", tmpDir)
+		err := os.RemoveAll(tmpDir)
+		if err != nil {
+			// On windows, if we remove too quickly the llama.dll may still be in-use and fail to remove
+			time.Sleep(1000 * time.Millisecond)
+			err = os.RemoveAll(tmpDir)
+			if err != nil {
+				slog.Warn("failed to clean up", "dir", tmpDir, "err", err)
+			}
+		}
+	}
+}
+
+func UpdatePath(dir string) {
+	if runtime.GOOS == "windows" {
+		tmpDir := filepath.Dir(dir)
+		pathComponents := strings.Split(os.Getenv("PATH"), ";")
+		i := 0
+		for _, comp := range pathComponents {
+			if strings.EqualFold(comp, dir) {
+				return
+			}
+			// Remove any other prior paths to our temp dir
+			if !strings.HasPrefix(strings.ToLower(comp), strings.ToLower(tmpDir)) {
+				pathComponents[i] = comp
+				i++
+			}
+		}
+		newPath := strings.Join(append([]string{dir}, pathComponents...), ";")
+		slog.Info("updating", "PATH", newPath)
+		os.Setenv("PATH", newPath)
+	}
+	// linux and darwin rely on rpath
+}

gpu/cuda_common.go

@@ -0,0 +1,22 @@
+//go:build linux || windows
+
+package gpu
+
+import (
+	"log/slog"
+	"strings"
+)
+
+func cudaGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
+	ids := []string{}
+	for _, info := range gpuInfo {
+		if info.Library != "cuda" {
+			// TODO shouldn't happen if things are wired correctly...
+			slog.Debug("cudaGetVisibleDevicesEnv skipping over non-cuda device", "library", info.Library)
+			continue
+		}
+		ids = append(ids, info.ID)
+	}
+	return "CUDA_VISIBLE_DEVICES", strings.Join(ids, ",")
+
+}

gpu/gpu.go

@@ -16,111 +16,109 @@ import (
 	"os"
 	"path/filepath"
 	"runtime"
-	"strconv"
 	"strings"
 	"sync"
 	"unsafe"
+
+	"github.com/ollama/ollama/format"
 )
 
 type handles struct {
-	cuda *C.cuda_handle_t
-	rocm *C.rocm_handle_t
+	deviceCount int
+	cudart      *C.cudart_handle_t
 }
 
+const (
+	cudaMinimumMemory = 457 * format.MebiByte
+	rocmMinimumMemory = 457 * format.MebiByte
+)
+
 var gpuMutex sync.Mutex
-var gpuHandles *handles = nil
 
 // With our current CUDA compile flags, older than 5.0 will not work properly
 var CudaComputeMin = [2]C.int{5, 0}
 
-// Possible locations for the nvidia-ml library
-var CudaLinuxGlobs = []string{
-	"/usr/local/cuda/lib64/libnvidia-ml.so*",
-	"/usr/lib/x86_64-linux-gnu/nvidia/current/libnvidia-ml.so*",
-	"/usr/lib/x86_64-linux-gnu/libnvidia-ml.so*",
-	"/usr/lib/wsl/lib/libnvidia-ml.so*",
-	"/usr/lib/wsl/drivers/*/libnvidia-ml.so*",
-	"/opt/cuda/lib64/libnvidia-ml.so*",
-	"/usr/lib*/libnvidia-ml.so*",
-	"/usr/local/lib*/libnvidia-ml.so*",
-	"/usr/lib/aarch64-linux-gnu/nvidia/current/libnvidia-ml.so*",
-	"/usr/lib/aarch64-linux-gnu/libnvidia-ml.so*",
+var RocmComputeMin = 9
 
-	// TODO: are these stubs ever valid?
-	"/opt/cuda/targets/x86_64-linux/lib/stubs/libnvidia-ml.so*",
+// TODO find a better way to detect iGPU instead of minimum memory
+const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU
+
+var CudartLinuxGlobs = []string{
+	"/usr/local/cuda/lib64/libcudart.so*",
+	"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
+	"/usr/lib/x86_64-linux-gnu/libcudart.so*",
+	"/usr/lib/wsl/lib/libcudart.so*",
+	"/usr/lib/wsl/drivers/*/libcudart.so*",
+	"/opt/cuda/lib64/libcudart.so*",
+	"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
+	"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
+	"/usr/lib/aarch64-linux-gnu/libcudart.so*",
+	"/usr/local/cuda/lib*/libcudart.so*",
+	"/usr/lib*/libcudart.so*",
+	"/usr/local/lib*/libcudart.so*",
 }
 
-var CudaWindowsGlobs = []string{
-	"c:\\Windows\\System32\\nvml.dll",
+var CudartWindowsGlobs = []string{
+	"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
 }
 
-var RocmLinuxGlobs = []string{
-	"/opt/rocm*/lib*/librocm_smi64.so*",
-}
-
-var RocmWindowsGlobs = []string{
-	"c:\\Windows\\System32\\rocm_smi64.dll",
-}
+// Jetson devices have JETSON_JETPACK="x.y.z" factory set to the Jetpack version installed.
+// Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices.
+var CudaTegra string = os.Getenv("JETSON_JETPACK")
 
 // Note: gpuMutex must already be held
-func initGPUHandles() {
+func initGPUHandles() *handles {
 
 	// TODO - if the ollama build is CPU only, don't do these checks as they're irrelevant and confusing
 
-	gpuHandles = &handles{nil, nil}
-	var cudaMgmtName string
-	var cudaMgmtPatterns []string
-	var rocmMgmtName string
-	var rocmMgmtPatterns []string
+	gpuHandles := &handles{}
+	var cudartMgmtName string
+	var cudartMgmtPatterns []string
+
+	tmpDir, _ := PayloadsDir()
 	switch runtime.GOOS {
 	case "windows":
-		cudaMgmtName = "nvml.dll"
-		cudaMgmtPatterns = make([]string, len(CudaWindowsGlobs))
-		copy(cudaMgmtPatterns, CudaWindowsGlobs)
-		rocmMgmtName = "rocm_smi64.dll"
-		rocmMgmtPatterns = make([]string, len(RocmWindowsGlobs))
-		copy(rocmMgmtPatterns, RocmWindowsGlobs)
+		cudartMgmtName = "cudart64_*.dll"
+		localAppData := os.Getenv("LOCALAPPDATA")
+		cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", cudartMgmtName)}
+		cudartMgmtPatterns = append(cudartMgmtPatterns, CudartWindowsGlobs...)
 	case "linux":
-		cudaMgmtName = "libnvidia-ml.so"
-		cudaMgmtPatterns = make([]string, len(CudaLinuxGlobs))
-		copy(cudaMgmtPatterns, CudaLinuxGlobs)
-		rocmMgmtName = "librocm_smi64.so"
-		rocmMgmtPatterns = make([]string, len(RocmLinuxGlobs))
-		copy(rocmMgmtPatterns, RocmLinuxGlobs)
+		cudartMgmtName = "libcudart.so*"
+		if tmpDir != "" {
+			// TODO - add "payloads" for subprocess
+			cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", cudartMgmtName)}
+		}
+		cudartMgmtPatterns = append(cudartMgmtPatterns, CudartLinuxGlobs...)
 	default:
-		return
+		return gpuHandles
 	}
 
-	slog.Info("Detecting GPU type")
-	cudaLibPaths := FindGPULibs(cudaMgmtName, cudaMgmtPatterns)
-	if len(cudaLibPaths) > 0 {
-		cuda := LoadCUDAMgmt(cudaLibPaths)
-		if cuda != nil {
-			slog.Info("Nvidia GPU detected")
-			gpuHandles.cuda = cuda
-			return
-		}
-	}
-
-	rocmLibPaths := FindGPULibs(rocmMgmtName, rocmMgmtPatterns)
-	if len(rocmLibPaths) > 0 {
-		rocm := LoadROCMMgmt(rocmLibPaths)
-		if rocm != nil {
-			slog.Info("Radeon GPU detected")
-			gpuHandles.rocm = rocm
-			return
+	slog.Info("Detecting GPUs")
+	cudartLibPaths := FindGPULibs(cudartMgmtName, cudartMgmtPatterns)
+	if len(cudartLibPaths) > 0 {
+		deviceCount, cudart, libPath := LoadCUDARTMgmt(cudartLibPaths)
+		if cudart != nil {
+			slog.Info("detected GPUs", "library", libPath, "count", deviceCount)
+			gpuHandles.cudart = cudart
+			gpuHandles.deviceCount = deviceCount
+			return gpuHandles
 		}
 	}
+	return gpuHandles
 }
 
-func GetGPUInfo() GpuInfo {
+func GetGPUInfo() GpuInfoList {
 	// TODO - consider exploring lspci (and equivalent on windows) to check for
 	// GPUs so we can report warnings if we see Nvidia/AMD but fail to load the libraries
 	gpuMutex.Lock()
 	defer gpuMutex.Unlock()
-	if gpuHandles == nil {
-		initGPUHandles()
-	}
+
+	gpuHandles := initGPUHandles()
+	defer func() {
+		if gpuHandles.cudart != nil {
+			C.cudart_release(*gpuHandles.cudart)
+		}
+	}()
 
 	// All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX
 	cpuVariant := GetCPUVariant()
@@ -129,106 +127,63 @@ func GetGPUInfo() GpuInfo {
 	}
 
 	var memInfo C.mem_info_t
-	resp := GpuInfo{}
-	if gpuHandles.cuda != nil && (cpuVariant != "" || runtime.GOARCH != "amd64") {
-		C.cuda_check_vram(*gpuHandles.cuda, &memInfo)
+	resp := []GpuInfo{}
+
+	// NVIDIA first
+	for i := 0; i < gpuHandles.deviceCount; i++ {
+		// TODO once we support CPU compilation variants of GPU libraries refine this...
+		if cpuVariant == "" && runtime.GOARCH == "amd64" {
+			continue
+		}
+		gpuInfo := GpuInfo{
+			Library: "cuda",
+		}
+		C.cudart_check_vram(*gpuHandles.cudart, C.int(i), &memInfo)
 		if memInfo.err != nil {
-			slog.Info(fmt.Sprintf("error looking up CUDA GPU memory: %s", C.GoString(memInfo.err)))
+			slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
 			C.free(unsafe.Pointer(memInfo.err))
-		} else if memInfo.count > 0 {
-			// Verify minimum compute capability
-			var cc C.cuda_compute_capability_t
-			C.cuda_compute_capability(*gpuHandles.cuda, &cc)
-			if cc.err != nil {
-				slog.Info(fmt.Sprintf("error looking up CUDA GPU compute capability: %s", C.GoString(cc.err)))
-				C.free(unsafe.Pointer(cc.err))
-			} else if cc.major > CudaComputeMin[0] || (cc.major == CudaComputeMin[0] && cc.minor >= CudaComputeMin[1]) {
-				slog.Info(fmt.Sprintf("CUDA Compute Capability detected: %d.%d", cc.major, cc.minor))
-				resp.Library = "cuda"
-			} else {
-				slog.Info(fmt.Sprintf("CUDA GPU is too old. Falling back to CPU mode. Compute Capability detected: %d.%d", cc.major, cc.minor))
-			}
+			continue
 		}
-	} else if AMDDetected() && gpuHandles.rocm != nil && (cpuVariant != "" || runtime.GOARCH != "amd64") {
-		ver, err := AMDDriverVersion()
-		if err == nil {
-			slog.Info("AMD Driver: " + ver)
-		} else {
-			// For now this is benign, but we may eventually need to fail compatibility checks
-			slog.Debug("error looking up amd driver version: %s", err)
+		if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) {
+			slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
+			continue
 		}
-		gfx := AMDGFXVersions()
-		tooOld := false
-		for _, v := range gfx {
-			if v.Major < 9 {
-				slog.Info("AMD GPU too old, falling back to CPU " + v.ToGFXString())
-				tooOld = true
-				break
-			}
+		gpuInfo.TotalMemory = uint64(memInfo.total)
+		gpuInfo.FreeMemory = uint64(memInfo.free)
+		gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
+		gpuInfo.Major = int(memInfo.major)
+		gpuInfo.Minor = int(memInfo.minor)
+		gpuInfo.MinimumMemory = cudaMinimumMemory
 
-			// TODO - remap gfx strings for unsupporetd minor/patch versions to supported for the same major
-			// e.g. gfx1034 works if we map it to gfx1030 at runtime
-
-		}
-		if !tooOld {
-			// TODO - this algo can be shifted over to use sysfs instead of the rocm info library...
-			C.rocm_check_vram(*gpuHandles.rocm, &memInfo)
-			if memInfo.err != nil {
-				slog.Info(fmt.Sprintf("error looking up ROCm GPU memory: %s", C.GoString(memInfo.err)))
-				C.free(unsafe.Pointer(memInfo.err))
-			} else if memInfo.igpu_index >= 0 && memInfo.count == 1 {
-				// Only one GPU detected and it appears to be an integrated GPU - skip it
-				slog.Info("ROCm unsupported integrated GPU detected")
-			} else if memInfo.count > 0 {
-				if memInfo.igpu_index >= 0 {
-					// We have multiple GPUs reported, and one of them is an integrated GPU
-					// so we have to set the env var to bypass it
-					// If the user has specified their own ROCR_VISIBLE_DEVICES, don't clobber it
-					val := os.Getenv("ROCR_VISIBLE_DEVICES")
-					if val == "" {
-						devices := []string{}
-						for i := 0; i < int(memInfo.count); i++ {
-							if i == int(memInfo.igpu_index) {
-								continue
-							}
-							devices = append(devices, strconv.Itoa(i))
-						}
-						val = strings.Join(devices, ",")
-						os.Setenv("ROCR_VISIBLE_DEVICES", val)
-					}
-					slog.Info(fmt.Sprintf("ROCm integrated GPU detected - ROCR_VISIBLE_DEVICES=%s", val))
-				}
-				resp.Library = "rocm"
-				var version C.rocm_version_resp_t
-				C.rocm_get_version(*gpuHandles.rocm, &version)
-				verString := C.GoString(version.str)
-				if version.status == 0 {
-					resp.Variant = "v" + verString
-				} else {
-					slog.Info(fmt.Sprintf("failed to look up ROCm version: %s", verString))
-				}
-				C.free(unsafe.Pointer(version.str))
-			}
-		}
+		// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
+		resp = append(resp, gpuInfo)
 	}
-	if resp.Library == "" {
+
+	// Then AMD
+	resp = append(resp, AMDGetGPUInfo()...)
+
+	if len(resp) == 0 {
 		C.cpu_check_ram(&memInfo)
-		resp.Library = "cpu"
-		resp.Variant = cpuVariant
-	}
-	if memInfo.err != nil {
-		slog.Info(fmt.Sprintf("error looking up CPU memory: %s", C.GoString(memInfo.err)))
-		C.free(unsafe.Pointer(memInfo.err))
-		return resp
+		if memInfo.err != nil {
+			slog.Info("error looking up CPU memory", "error", C.GoString(memInfo.err))
+			C.free(unsafe.Pointer(memInfo.err))
+			return resp
+		}
+		gpuInfo := GpuInfo{
+			Library: "cpu",
+			Variant: cpuVariant,
+		}
+		gpuInfo.TotalMemory = uint64(memInfo.total)
+		gpuInfo.FreeMemory = uint64(memInfo.free)
+		gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
+
+		resp = append(resp, gpuInfo)
 	}
 
-	resp.DeviceCount = uint32(memInfo.count)
-	resp.FreeMemory = uint64(memInfo.free)
-	resp.TotalMemory = uint64(memInfo.total)
 	return resp
 }
 
-func getCPUMem() (memInfo, error) {
+func GetCPUMem() (memInfo, error) {
 	var ret memInfo
 	var info C.mem_info_t
 	C.cpu_check_ram(&info)
@@ -241,28 +196,11 @@ func getCPUMem() (memInfo, error) {
 	return ret, nil
 }
 
-func CheckVRAM() (int64, error) {
-	gpuInfo := GetGPUInfo()
-	if gpuInfo.FreeMemory > 0 && (gpuInfo.Library == "cuda" || gpuInfo.Library == "rocm") {
-		// leave 10% or 1024MiB of VRAM free per GPU to handle unaccounted for overhead
-		overhead := gpuInfo.FreeMemory / 10
-		gpus := uint64(gpuInfo.DeviceCount)
-		if overhead < gpus*1024*1024*1024 {
-			overhead = gpus * 1024 * 1024 * 1024
-		}
-		avail := int64(gpuInfo.FreeMemory - overhead)
-		slog.Debug(fmt.Sprintf("%s detected %d devices with %dM available memory", gpuInfo.Library, gpuInfo.DeviceCount, avail/1024/1024))
-		return avail, nil
-	}
-
-	return 0, fmt.Errorf("no GPU detected") // TODO - better handling of CPU based memory determiniation
-}
-
 func FindGPULibs(baseLibName string, patterns []string) []string {
 	// Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them
 	var ldPaths []string
 	gpuLibPaths := []string{}
-	slog.Info(fmt.Sprintf("Searching for GPU management library %s", baseLibName))
+	slog.Debug("Searching for GPU library", "name", baseLibName)
 
 	switch runtime.GOOS {
 	case "windows":
@@ -280,7 +218,7 @@ func FindGPULibs(baseLibName string, patterns []string) []string {
 		}
 		patterns = append(patterns, filepath.Join(d, baseLibName+"*"))
 	}
-	slog.Debug(fmt.Sprintf("gpu management search paths: %v", patterns))
+	slog.Debug("gpu library search", "globs", patterns)
 	for _, pattern := range patterns {
 		// Ignore glob discovery errors
 		matches, _ := filepath.Glob(pattern)
@@ -308,42 +246,25 @@ func FindGPULibs(baseLibName string, patterns []string) []string {
 			}
 		}
 	}
-	slog.Info(fmt.Sprintf("Discovered GPU libraries: %v", gpuLibPaths))
+	slog.Debug("discovered GPU libraries", "paths", gpuLibPaths)
 	return gpuLibPaths
 }
 
-func LoadCUDAMgmt(cudaLibPaths []string) *C.cuda_handle_t {
-	var resp C.cuda_init_resp_t
+func LoadCUDARTMgmt(cudartLibPaths []string) (int, *C.cudart_handle_t, string) {
+	var resp C.cudart_init_resp_t
 	resp.ch.verbose = getVerboseState()
-	for _, libPath := range cudaLibPaths {
+	for _, libPath := range cudartLibPaths {
 		lib := C.CString(libPath)
 		defer C.free(unsafe.Pointer(lib))
-		C.cuda_init(lib, &resp)
+		C.cudart_init(lib, &resp)
 		if resp.err != nil {
-			slog.Info(fmt.Sprintf("Unable to load CUDA management library %s: %s", libPath, C.GoString(resp.err)))
+			slog.Debug("Unable to load cudart", "library", libPath, "error", C.GoString(resp.err))
 			C.free(unsafe.Pointer(resp.err))
 		} else {
-			return &resp.ch
+			return int(resp.num_devices), &resp.ch, libPath
 		}
 	}
-	return nil
-}
-
-func LoadROCMMgmt(rocmLibPaths []string) *C.rocm_handle_t {
-	var resp C.rocm_init_resp_t
-	resp.rh.verbose = getVerboseState()
-	for _, libPath := range rocmLibPaths {
-		lib := C.CString(libPath)
-		defer C.free(unsafe.Pointer(lib))
-		C.rocm_init(lib, &resp)
-		if resp.err != nil {
-			slog.Info(fmt.Sprintf("Unable to load ROCm management library %s: %s", libPath, C.GoString(resp.err)))
-			C.free(unsafe.Pointer(resp.err))
-		} else {
-			return &resp.rh
-		}
-	}
-	return nil
+	return 0, nil, ""
 }
 
 func getVerboseState() C.uint16_t {
@@ -352,3 +273,22 @@ func getVerboseState() C.uint16_t {
 	}
 	return C.uint16_t(0)
 }
+
+// Given the list of GPUs this instantiation is targeted for,
+// figure out the visible devices environment variable
+//
+// If different libraries are detected, the first one is what we use
+func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
+	if len(l) == 0 {
+		return "", ""
+	}
+	switch l[0].Library {
+	case "cuda":
+		return cudaGetVisibleDevicesEnv(l)
+	case "rocm":
+		return rocmGetVisibleDevicesEnv(l)
+	default:
+		slog.Debug("no filter required for library " + l[0].Library)
+		return "", ""
+	}
+}

gpu/gpu_darwin.go

@@ -2,53 +2,48 @@
 
 package gpu
 
+/*
+#cgo CFLAGS: -x objective-c
+#cgo LDFLAGS: -framework Foundation -framework CoreGraphics -framework Metal
+#include "gpu_info_darwin.h"
+*/
 import "C"
 import (
 	"runtime"
-
-	"github.com/pbnjay/memory"
 )
 
-// CheckVRAM returns the free VRAM in bytes on Linux machines with NVIDIA GPUs
-func CheckVRAM() (int64, error) {
+func GetGPUInfo() GpuInfoList {
+	mem, _ := GetCPUMem()
 	if runtime.GOARCH == "amd64" {
-		// gpu not supported, this may not be metal
-		return 0, nil
-	}
-
-	// on macOS, there's already buffer for available vram (see below) so just return the total
-	systemMemory := int64(memory.TotalMemory())
-
-	// macOS limits how much memory is available to the GPU based on the amount of system memory
-	// TODO: handle case where iogpu.wired_limit_mb is set to a higher value
-	if systemMemory <= 36*1024*1024*1024 {
-		systemMemory = systemMemory * 2 / 3
-	} else {
-		systemMemory = systemMemory * 3 / 4
-	}
-
-	return systemMemory, nil
-}
-
-func GetGPUInfo() GpuInfo {
-	mem, _ := getCPUMem()
-	if runtime.GOARCH == "amd64" {
-		return GpuInfo{
-			Library: "cpu",
-			Variant: GetCPUVariant(),
-			memInfo: mem,
+		return []GpuInfo{
+			{
+				Library: "cpu",
+				Variant: GetCPUVariant(),
+				memInfo: mem,
+			},
 		}
 	}
-	return GpuInfo{
+	info := GpuInfo{
 		Library: "metal",
-		memInfo: mem,
+		ID:      "0",
 	}
+	info.TotalMemory = uint64(C.getRecommendedMaxVRAM())
+
+	// TODO is there a way to gather actual allocated video memory? (currentAllocatedSize doesn't work)
+	info.FreeMemory = info.TotalMemory
+
+	info.MinimumMemory = 0
+	return []GpuInfo{info}
 }
 
-func getCPUMem() (memInfo, error) {
+func GetCPUMem() (memInfo, error) {
 	return memInfo{
-		TotalMemory: 0,
+		TotalMemory: uint64(C.getPhysicalMemory()),
 		FreeMemory:  0,
-		DeviceCount: 0,
 	}, nil
 }
+
+func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
+	// No-op on darwin
+	return "", ""
+}

gpu/gpu_info.h

@@ -38,12 +38,17 @@
 extern "C" {
 #endif
 
+#define GPU_ID_LEN 64
+
 typedef struct mem_info {
+  char *err;  // If non-nill, caller responsible for freeing
+  char gpu_id[GPU_ID_LEN];
   uint64_t total;
   uint64_t free;
-  unsigned int count;
-  int igpu_index; // If >= 0, we detected an integrated GPU to ignore
-  char *err;  // If non-nill, caller responsible for freeing
+
+  // Compute Capability
+  int major; 
+  int minor;
 } mem_info_t;
 
 void cpu_check_ram(mem_info_t *resp);
@@ -52,8 +57,7 @@ void cpu_check_ram(mem_info_t *resp);
 }
 #endif
 
-#include "gpu_info_cuda.h"
-#include "gpu_info_rocm.h"
+#include "gpu_info_cudart.h"
 
 #endif  // __GPU_INFO_H__
 #endif  // __APPLE__

gpu/gpu_info_cpu.c

@@ -8,9 +8,11 @@ void cpu_check_ram(mem_info_t *resp) {
   MEMORYSTATUSEX info;
   info.dwLength = sizeof(info);
   if (GlobalMemoryStatusEx(&info) != 0) {
-    resp->count = 1;
     resp->total = info.ullTotalPhys;
     resp->free = info.ullAvailPhys;
+    resp->major = 0;
+    resp->minor = 0;
+    snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
   } else {
     resp->err = LOAD_ERR();
   }
@@ -27,9 +29,11 @@ void cpu_check_ram(mem_info_t *resp) {
   if (sysinfo(&info) != 0) {
     resp->err = strdup(strerror(errno));
   } else {
-    resp->count = 1;
     resp->total = info.totalram * info.mem_unit;
     resp->free = info.freeram * info.mem_unit;
+    resp->major = 0;
+    resp->minor = 0;
+    snprintf(&resp->gpu_id[0], GPU_ID_LEN, "0");
   }
   return;
 }

gpu/gpu_info_cuda.c

@@ -1,214 +0,0 @@
-#ifndef __APPLE__  // TODO - maybe consider nvidia support on intel macs?
-
-#include "gpu_info_cuda.h"
-
-#include <string.h>
-
-void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp) {
-  nvmlReturn_t ret;
-  resp->err = NULL;
-  const int buflen = 256;
-  char buf[buflen + 1];
-  int i;
-
-  struct lookup {
-    char *s;
-    void **p;
-  } l[] = {
-      {"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
-      {"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
-      {"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.nvmlDeviceGetHandleByIndex},
-      {"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
-      {"nvmlDeviceGetCount_v2", (void *)&resp->ch.nvmlDeviceGetCount_v2},
-      {"nvmlDeviceGetCudaComputeCapability", (void *)&resp->ch.nvmlDeviceGetCudaComputeCapability},
-      {"nvmlSystemGetDriverVersion", (void *)&resp->ch.nvmlSystemGetDriverVersion},
-      {"nvmlDeviceGetName", (void *)&resp->ch.nvmlDeviceGetName},
-      {"nvmlDeviceGetSerial", (void *)&resp->ch.nvmlDeviceGetSerial},
-      {"nvmlDeviceGetVbiosVersion", (void *)&resp->ch.nvmlDeviceGetVbiosVersion},
-      {"nvmlDeviceGetBoardPartNumber", (void *)&resp->ch.nvmlDeviceGetBoardPartNumber},
-      {"nvmlDeviceGetBrand", (void *)&resp->ch.nvmlDeviceGetBrand},
-      {NULL, NULL},
-  };
-
-  resp->ch.handle = LOAD_LIBRARY(cuda_lib_path, RTLD_LAZY);
-  if (!resp->ch.handle) {
-    char *msg = LOAD_ERR();
-    LOG(resp->ch.verbose, "library %s load err: %s\n", cuda_lib_path, msg);
-    snprintf(buf, buflen,
-             "Unable to load %s library to query for Nvidia GPUs: %s",
-             cuda_lib_path, msg);
-    free(msg);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  // TODO once we've squashed the remaining corner cases remove this log
-  LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", cuda_lib_path);
-  
-  for (i = 0; l[i].s != NULL; i++) {
-    // TODO once we've squashed the remaining corner cases remove this log
-    LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
-
-    *l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
-    if (!l[i].p) {
-      resp->ch.handle = NULL;
-      char *msg = LOAD_ERR();
-      LOG(resp->ch.verbose, "dlerr: %s\n", msg);
-      UNLOAD_LIBRARY(resp->ch.handle);
-      snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
-               msg);
-      free(msg);
-      resp->err = strdup(buf);
-      return;
-    }
-  }
-
-  ret = (*resp->ch.nvmlInit_v2)();
-  if (ret != NVML_SUCCESS) {
-    LOG(resp->ch.verbose, "nvmlInit_v2 err: %d\n", ret);
-    UNLOAD_LIBRARY(resp->ch.handle);
-    resp->ch.handle = NULL;
-    snprintf(buf, buflen, "nvml vram init failure: %d", ret);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  // Report driver version if we're in verbose mode, ignore errors
-  ret = (*resp->ch.nvmlSystemGetDriverVersion)(buf, buflen);
-  if (ret != NVML_SUCCESS) {
-    LOG(resp->ch.verbose, "nvmlSystemGetDriverVersion failed: %d\n", ret);
-  } else {
-    LOG(resp->ch.verbose, "CUDA driver version: %s\n", buf);
-  }
-}
-
-void cuda_check_vram(cuda_handle_t h, mem_info_t *resp) {
-  resp->err = NULL;
-  nvmlDevice_t device;
-  nvmlMemory_t memInfo = {0};
-  nvmlReturn_t ret;
-  const int buflen = 256;
-  char buf[buflen + 1];
-  int i;
-
-  if (h.handle == NULL) {
-    resp->err = strdup("nvml handle sn't initialized");
-    return;
-  }
-
-  ret = (*h.nvmlDeviceGetCount_v2)(&resp->count);
-  if (ret != NVML_SUCCESS) {
-    snprintf(buf, buflen, "unable to get device count: %d", ret);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  resp->total = 0;
-  resp->free = 0;
-  for (i = 0; i < resp->count; i++) {
-    ret = (*h.nvmlDeviceGetHandleByIndex)(i, &device);
-    if (ret != NVML_SUCCESS) {
-      snprintf(buf, buflen, "unable to get device handle %d: %d", i, ret);
-      resp->err = strdup(buf);
-      return;
-    }
-
-    ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
-    if (ret != NVML_SUCCESS) {
-      snprintf(buf, buflen, "device memory info lookup failure %d: %d", i, ret);
-      resp->err = strdup(buf);
-      return;
-    }
-    if (h.verbose) {
-      nvmlBrandType_t brand = 0;
-      // When in verbose mode, report more information about
-      // the card we discover, but don't fail on error
-      ret = (*h.nvmlDeviceGetName)(device, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "nvmlDeviceGetName failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] CUDA device name: %s\n", i, buf);
-      }
-      ret = (*h.nvmlDeviceGetBoardPartNumber)(device, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "nvmlDeviceGetBoardPartNumber failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] CUDA part number: %s\n", i, buf);
-      }
-      ret = (*h.nvmlDeviceGetSerial)(device, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "nvmlDeviceGetSerial failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] CUDA S/N: %s\n", i, buf);
-      }
-      ret = (*h.nvmlDeviceGetVbiosVersion)(device, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "nvmlDeviceGetVbiosVersion failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] CUDA vbios version: %s\n", i, buf);
-      }
-      ret = (*h.nvmlDeviceGetBrand)(device, &brand);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "nvmlDeviceGetBrand failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] CUDA brand: %d\n", i, brand);
-      }
-    }
-
-    LOG(h.verbose, "[%d] CUDA totalMem %ld\n", i, memInfo.total);
-    LOG(h.verbose, "[%d] CUDA usedMem %ld\n", i, memInfo.free);
-
-    resp->total += memInfo.total;
-    resp->free += memInfo.free;
-  }
-}
-
-void cuda_compute_capability(cuda_handle_t h, cuda_compute_capability_t *resp) {
-  resp->err = NULL;
-  resp->major = 0;
-  resp->minor = 0;
-  nvmlDevice_t device;
-  int major = 0;
-  int minor = 0;
-  nvmlReturn_t ret;
-  const int buflen = 256;
-  char buf[buflen + 1];
-  int i;
-
-  if (h.handle == NULL) {
-    resp->err = strdup("nvml handle not initialized");
-    return;
-  }
-
-  unsigned int devices;
-  ret = (*h.nvmlDeviceGetCount_v2)(&devices);
-  if (ret != NVML_SUCCESS) {
-    snprintf(buf, buflen, "unable to get device count: %d", ret);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  for (i = 0; i < devices; i++) {
-    ret = (*h.nvmlDeviceGetHandleByIndex)(i, &device);
-    if (ret != NVML_SUCCESS) {
-      snprintf(buf, buflen, "unable to get device handle %d: %d", i, ret);
-      resp->err = strdup(buf);
-      return;
-    }
-
-    ret = (*h.nvmlDeviceGetCudaComputeCapability)(device, &major, &minor);
-    if (ret != NVML_SUCCESS) {
-      snprintf(buf, buflen, "device compute capability lookup failure %d: %d", i, ret);
-      resp->err = strdup(buf);
-      return;
-    }
-    // Report the lowest major.minor we detect as that limits our compatibility
-    if (resp->major == 0 || resp->major > major ) {
-      resp->major = major;
-      resp->minor = minor;
-    } else if ( resp->major == major && resp->minor > minor ) {
-      resp->minor = minor;
-    }
-  }
-}
-#endif  // __APPLE__

gpu/gpu_info_cuda.h

@@ -1,56 +0,0 @@
-#ifndef __APPLE__
-#ifndef __GPU_INFO_CUDA_H__
-#define __GPU_INFO_CUDA_H__
-#include "gpu_info.h"
-
-// Just enough typedef's to dlopen/dlsym for memory information
-typedef enum nvmlReturn_enum {
-  NVML_SUCCESS = 0,
-  // Other values omitted for now...
-} nvmlReturn_t;
-typedef void *nvmlDevice_t;  // Opaque is sufficient
-typedef struct nvmlMemory_st {
-  unsigned long long total;
-  unsigned long long free;
-  unsigned long long used;
-} nvmlMemory_t;
-
-typedef enum nvmlBrandType_enum
-{
-    NVML_BRAND_UNKNOWN          = 0,
-} nvmlBrandType_t;
-
-typedef struct cuda_handle {
-  void *handle;
-  uint16_t verbose;
-  nvmlReturn_t (*nvmlInit_v2)(void);
-  nvmlReturn_t (*nvmlShutdown)(void);
-  nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t *);
-  nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
-  nvmlReturn_t (*nvmlDeviceGetCount_v2)(unsigned int *);
-  nvmlReturn_t (*nvmlDeviceGetCudaComputeCapability)(nvmlDevice_t, int* major, int* minor);
-  nvmlReturn_t (*nvmlSystemGetDriverVersion) (char* version, unsigned int  length);
-  nvmlReturn_t (*nvmlDeviceGetName) (nvmlDevice_t device, char* name, unsigned int  length);
-  nvmlReturn_t (*nvmlDeviceGetSerial) (nvmlDevice_t device, char* serial, unsigned int  length);
-  nvmlReturn_t (*nvmlDeviceGetVbiosVersion) (nvmlDevice_t device, char* version, unsigned int  length);
-  nvmlReturn_t (*nvmlDeviceGetBoardPartNumber) (nvmlDevice_t device, char* partNumber, unsigned int  length);
-  nvmlReturn_t (*nvmlDeviceGetBrand) (nvmlDevice_t device, nvmlBrandType_t* type);
-} cuda_handle_t;
-
-typedef struct cuda_init_resp {
-  char *err;  // If err is non-null handle is invalid
-  cuda_handle_t ch;
-} cuda_init_resp_t;
-
-typedef struct cuda_compute_capability {
-  char *err;
-  int major;
-  int minor;
-} cuda_compute_capability_t;
-
-void cuda_init(char *cuda_lib_path, cuda_init_resp_t *resp);
-void cuda_check_vram(cuda_handle_t ch, mem_info_t *resp);
-void cuda_compute_capability(cuda_handle_t ch, cuda_compute_capability_t *cc);
-
-#endif  // __GPU_INFO_CUDA_H__
-#endif  // __APPLE__

gpu/gpu_info_cudart.c

@@ -0,0 +1,181 @@
+#ifndef __APPLE__  // TODO - maybe consider nvidia support on intel macs?
+
+#include <string.h>
+#include "gpu_info_cudart.h"
+
+void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
+  cudartReturn_t ret;
+  resp->err = NULL;
+  resp->num_devices = 0;
+  const int buflen = 256;
+  char buf[buflen + 1];
+  int i;
+
+  struct lookup {
+    char *s;
+    void **p;
+  } l[] = {
+      {"cudaSetDevice", (void *)&resp->ch.cudaSetDevice},
+      {"cudaDeviceSynchronize", (void *)&resp->ch.cudaDeviceSynchronize},
+      {"cudaDeviceReset", (void *)&resp->ch.cudaDeviceReset},
+      {"cudaMemGetInfo", (void *)&resp->ch.cudaMemGetInfo},
+      {"cudaGetDeviceCount", (void *)&resp->ch.cudaGetDeviceCount},
+      {"cudaDeviceGetAttribute", (void *)&resp->ch.cudaDeviceGetAttribute},
+      {"cudaDriverGetVersion", (void *)&resp->ch.cudaDriverGetVersion},
+      {"cudaGetDeviceProperties", (void *)&resp->ch.cudaGetDeviceProperties},
+      {NULL, NULL},
+  };
+
+  resp->ch.handle = LOAD_LIBRARY(cudart_lib_path, RTLD_LAZY);
+  if (!resp->ch.handle) {
+    char *msg = LOAD_ERR();
+    LOG(resp->ch.verbose, "library %s load err: %s\n", cudart_lib_path, msg);
+    snprintf(buf, buflen,
+            "Unable to load %s library to query for Nvidia GPUs: %s",
+            cudart_lib_path, msg);
+    free(msg);
+    resp->err = strdup(buf);
+    return;
+  }
+
+  for (i = 0; l[i].s != NULL; i++) {
+    *l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
+    if (!l[i].p) {
+      char *msg = LOAD_ERR();
+      LOG(resp->ch.verbose, "dlerr: %s\n", msg);
+      UNLOAD_LIBRARY(resp->ch.handle);
+      resp->ch.handle = NULL;
+      snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
+              msg);
+      free(msg);
+      resp->err = strdup(buf);
+      return;
+    }
+  }
+
+  ret = (*resp->ch.cudaSetDevice)(0);
+  if (ret != CUDART_SUCCESS) {
+    LOG(resp->ch.verbose, "cudaSetDevice err: %d\n", ret);
+    UNLOAD_LIBRARY(resp->ch.handle);
+    resp->ch.handle = NULL;
+    if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
+      resp->err = strdup("your nvidia driver is too old or missing.  If you have a CUDA GPU please upgrade to run ollama");
+      return;
+    }
+    snprintf(buf, buflen, "cudart init failure: %d", ret);
+    resp->err = strdup(buf);
+    return;
+  }
+
+  int version = 0;
+  cudartDriverVersion_t driverVersion;
+  driverVersion.major = 0;
+  driverVersion.minor = 0;
+
+  // Report driver version if we're in verbose mode, ignore errors
+  ret = (*resp->ch.cudaDriverGetVersion)(&version);
+  if (ret != CUDART_SUCCESS) {
+    LOG(resp->ch.verbose, "cudaDriverGetVersion failed: %d\n", ret);
+  } else {
+    driverVersion.major = version / 1000;
+    driverVersion.minor = (version - (driverVersion.major * 1000)) / 10;
+    LOG(resp->ch.verbose, "CUDA driver version: %d-%d\n", driverVersion.major, driverVersion.minor);
+  }
+
+  ret = (*resp->ch.cudaGetDeviceCount)(&resp->num_devices);
+  if (ret != CUDART_SUCCESS) {
+    LOG(resp->ch.verbose, "cudaGetDeviceCount err: %d\n", ret);
+    UNLOAD_LIBRARY(resp->ch.handle);
+    resp->ch.handle = NULL;
+    snprintf(buf, buflen, "unable to get device count: %d", ret);
+    resp->err = strdup(buf);
+    return;
+  }
+}
+
+
+void cudart_check_vram(cudart_handle_t h, int i, mem_info_t *resp) {
+  resp->err = NULL;
+  cudartMemory_t memInfo = {0,0,0};
+  cudartReturn_t ret;
+  const int buflen = 256;
+  char buf[buflen + 1];
+
+  if (h.handle == NULL) {
+    resp->err = strdup("cudart handle isn't initialized");
+    return;
+  }
+
+  ret = (*h.cudaSetDevice)(i);
+  if (ret != CUDART_SUCCESS) {
+    snprintf(buf, buflen, "cudart device failed to initialize");
+    resp->err = strdup(buf);
+    return;
+  }
+
+  cudaDeviceProp_t props;
+  ret = (*h.cudaGetDeviceProperties)(&props, i);
+  if (ret != CUDART_SUCCESS) {
+    LOG(h.verbose, "[%d] device properties lookup failure: %d\n", i, ret);
+    snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", i);
+    resp->major = 0;
+    resp->minor = 0;
+  } else {
+    int allNull = 1;
+    for (int j = 0; j < 16; j++) {
+      if (props.uuid.bytes[j] != 0) {
+        allNull = 0;
+        break;
+      }
+    }
+    if (allNull != 0) {
+      snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", i);
+    } else {
+      // GPU-d110a105-ac29-1d54-7b49-9c90440f215b
+      snprintf(&resp->gpu_id[0], GPU_ID_LEN,
+          "GPU-%02x%02x%02x%02x-%02x%02x-%02x%02x-%02x%02x-%02x%02x%02x%02x%02x%02x",
+          props.uuid.bytes[0],
+          props.uuid.bytes[1],
+          props.uuid.bytes[2],
+          props.uuid.bytes[3],
+          props.uuid.bytes[4],
+          props.uuid.bytes[5],
+          props.uuid.bytes[6],
+          props.uuid.bytes[7],
+          props.uuid.bytes[8],
+          props.uuid.bytes[9],
+          props.uuid.bytes[10],
+          props.uuid.bytes[11],
+          props.uuid.bytes[12],
+          props.uuid.bytes[13],
+          props.uuid.bytes[14],
+          props.uuid.bytes[15]
+        );
+    }
+    resp->major = props.major;
+    resp->minor = props.minor;
+
+    // TODO add other useful properties from props
+  }
+  ret = (*h.cudaMemGetInfo)(&memInfo.free, &memInfo.total);
+  if (ret != CUDART_SUCCESS) {
+    snprintf(buf, buflen, "cudart device memory info lookup failure %d", ret);
+    resp->err = strdup(buf);
+    return;
+  }
+
+  resp->total = memInfo.total;
+  resp->free = memInfo.free;
+
+  LOG(h.verbose, "[%s] CUDA totalMem %lu\n", resp->gpu_id, resp->total);
+  LOG(h.verbose, "[%s] CUDA freeMem %lu\n", resp->gpu_id, resp->free);
+  LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
+}
+
+void cudart_release(cudart_handle_t h) {
+  LOG(h.verbose, "releasing cudart library\n");
+  UNLOAD_LIBRARY(h.handle);
+  h.handle = NULL;
+}
+
+#endif  // __APPLE__

gpu/gpu_info_cudart.h

@@ -0,0 +1,147 @@
+#ifndef __APPLE__
+#ifndef __GPU_INFO_CUDART_H__
+#define __GPU_INFO_CUDART_H__
+#include "gpu_info.h"
+
+// Just enough typedef's to dlopen/dlsym for memory information
+typedef enum cudartReturn_enum {
+  CUDART_SUCCESS = 0,
+  CUDA_ERROR_INVALID_VALUE = 1,
+  CUDA_ERROR_MEMORY_ALLOCATION = 2,
+  CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
+  // Other values omitted for now...
+} cudartReturn_t;
+
+typedef enum cudartDeviceAttr_enum {
+  cudartDevAttrComputeCapabilityMajor = 75,
+  cudartDevAttrComputeCapabilityMinor = 76,
+
+  // TODO - not yet wired up but may be useful for Jetson or other
+  // integrated GPU scenarios with shared memory
+  cudaDevAttrIntegrated = 18
+
+} cudartDeviceAttr_t;
+
+typedef void *cudartDevice_t;  // Opaque is sufficient
+typedef struct cudartMemory_st {
+  size_t total;
+  size_t free;
+  size_t used;
+} cudartMemory_t;
+
+typedef struct cudartDriverVersion {
+  int major;
+  int minor;
+} cudartDriverVersion_t;
+
+typedef struct cudaUUID {
+    unsigned char bytes[16];
+} cudaUUID_t;
+typedef struct cudaDeviceProp {
+    char         name[256];                  /**< ASCII string identifying device */
+    cudaUUID_t   uuid;                       /**< 16-byte unique identifier */
+    char         luid[8];                    /**< 8-byte locally unique identifier. Value is undefined on TCC and non-Windows platforms */
+    unsigned int luidDeviceNodeMask;         /**< LUID device node mask. Value is undefined on TCC and non-Windows platforms */
+    size_t       totalGlobalMem;             /**< Global memory available on device in bytes */
+    size_t       sharedMemPerBlock;          /**< Shared memory available per block in bytes */
+    int          regsPerBlock;               /**< 32-bit registers available per block */
+    int          warpSize;                   /**< Warp size in threads */
+    size_t       memPitch;                   /**< Maximum pitch in bytes allowed by memory copies */
+    int          maxThreadsPerBlock;         /**< Maximum number of threads per block */
+    int          maxThreadsDim[3];           /**< Maximum size of each dimension of a block */
+    int          maxGridSize[3];             /**< Maximum size of each dimension of a grid */
+    int          clockRate;                  /**< Clock frequency in kilohertz */
+    size_t       totalConstMem;              /**< Constant memory available on device in bytes */
+    int          major;                      /**< Major compute capability */
+    int          minor;                      /**< Minor compute capability */
+    size_t       textureAlignment;           /**< Alignment requirement for textures */
+    size_t       texturePitchAlignment;      /**< Pitch alignment requirement for texture references bound to pitched memory */
+    int          deviceOverlap;              /**< Device can concurrently copy memory and execute a kernel. Deprecated. Use instead asyncEngineCount. */
+    int          multiProcessorCount;        /**< Number of multiprocessors on device */
+    int          kernelExecTimeoutEnabled;   /**< Specified whether there is a run time limit on kernels */
+    int          integrated;                 /**< Device is integrated as opposed to discrete */
+    int          canMapHostMemory;           /**< Device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer */
+    int          computeMode;                /**< Compute mode (See ::cudaComputeMode) */
+    int          maxTexture1D;               /**< Maximum 1D texture size */
+    int          maxTexture1DMipmap;         /**< Maximum 1D mipmapped texture size */
+    int          maxTexture1DLinear;         /**< Deprecated, do not use. Use cudaDeviceGetTexture1DLinearMaxWidth() or cuDeviceGetTexture1DLinearMaxWidth() instead. */
+    int          maxTexture2D[2];            /**< Maximum 2D texture dimensions */
+    int          maxTexture2DMipmap[2];      /**< Maximum 2D mipmapped texture dimensions */
+    int          maxTexture2DLinear[3];      /**< Maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory */
+    int          maxTexture2DGather[2];      /**< Maximum 2D texture dimensions if texture gather operations have to be performed */
+    int          maxTexture3D[3];            /**< Maximum 3D texture dimensions */
+    int          maxTexture3DAlt[3];         /**< Maximum alternate 3D texture dimensions */
+    int          maxTextureCubemap;          /**< Maximum Cubemap texture dimensions */
+    int          maxTexture1DLayered[2];     /**< Maximum 1D layered texture dimensions */
+    int          maxTexture2DLayered[3];     /**< Maximum 2D layered texture dimensions */
+    int          maxTextureCubemapLayered[2];/**< Maximum Cubemap layered texture dimensions */
+    int          maxSurface1D;               /**< Maximum 1D surface size */
+    int          maxSurface2D[2];            /**< Maximum 2D surface dimensions */
+    int          maxSurface3D[3];            /**< Maximum 3D surface dimensions */
+    int          maxSurface1DLayered[2];     /**< Maximum 1D layered surface dimensions */
+    int          maxSurface2DLayered[3];     /**< Maximum 2D layered surface dimensions */
+    int          maxSurfaceCubemap;          /**< Maximum Cubemap surface dimensions */
+    int          maxSurfaceCubemapLayered[2];/**< Maximum Cubemap layered surface dimensions */
+    size_t       surfaceAlignment;           /**< Alignment requirements for surfaces */
+    int          concurrentKernels;          /**< Device can possibly execute multiple kernels concurrently */
+    int          ECCEnabled;                 /**< Device has ECC support enabled */
+    int          pciBusID;                   /**< PCI bus ID of the device */
+    int          pciDeviceID;                /**< PCI device ID of the device */
+    int          pciDomainID;                /**< PCI domain ID of the device */
+    int          tccDriver;                  /**< 1 if device is a Tesla device using TCC driver, 0 otherwise */
+    int          asyncEngineCount;           /**< Number of asynchronous engines */
+    int          unifiedAddressing;          /**< Device shares a unified address space with the host */
+    int          memoryClockRate;            /**< Peak memory clock frequency in kilohertz */
+    int          memoryBusWidth;             /**< Global memory bus width in bits */
+    int          l2CacheSize;                /**< Size of L2 cache in bytes */
+    int          persistingL2CacheMaxSize;   /**< Device's maximum l2 persisting lines capacity setting in bytes */
+    int          maxThreadsPerMultiProcessor;/**< Maximum resident threads per multiprocessor */
+    int          streamPrioritiesSupported;  /**< Device supports stream priorities */
+    int          globalL1CacheSupported;     /**< Device supports caching globals in L1 */
+    int          localL1CacheSupported;      /**< Device supports caching locals in L1 */
+    size_t       sharedMemPerMultiprocessor; /**< Shared memory available per multiprocessor in bytes */
+    int          regsPerMultiprocessor;      /**< 32-bit registers available per multiprocessor */
+    int          managedMemory;              /**< Device supports allocating managed memory on this system */
+    int          isMultiGpuBoard;            /**< Device is on a multi-GPU board */
+    int          multiGpuBoardGroupID;       /**< Unique identifier for a group of devices on the same multi-GPU board */
+    int          hostNativeAtomicSupported;  /**< Link between the device and the host supports native atomic operations */
+    int          singleToDoublePrecisionPerfRatio; /**< Ratio of single precision performance (in floating-point operations per second) to double precision performance */
+    int          pageableMemoryAccess;       /**< Device supports coherently accessing pageable memory without calling cudaHostRegister on it */
+    int          concurrentManagedAccess;    /**< Device can coherently access managed memory concurrently with the CPU */
+    int          computePreemptionSupported; /**< Device supports Compute Preemption */
+    int          canUseHostPointerForRegisteredMem; /**< Device can access host registered memory at the same virtual address as the CPU */
+    int          cooperativeLaunch;          /**< Device supports launching cooperative kernels via ::cudaLaunchCooperativeKernel */
+    int          cooperativeMultiDeviceLaunch; /**< Deprecated, cudaLaunchCooperativeKernelMultiDevice is deprecated. */
+    size_t       sharedMemPerBlockOptin;     /**< Per device maximum shared memory per block usable by special opt in */
+    int          pageableMemoryAccessUsesHostPageTables; /**< Device accesses pageable memory via the host's page tables */
+    int          directManagedMemAccessFromHost; /**< Host can directly access managed memory on the device without migration. */
+    int          maxBlocksPerMultiProcessor; /**< Maximum number of resident blocks per multiprocessor */
+    int          accessPolicyMaxWindowSize;  /**< The maximum value of ::cudaAccessPolicyWindow::num_bytes. */
+    size_t       reservedSharedMemPerBlock;  /**< Shared memory reserved by CUDA driver per block in bytes */
+  } cudaDeviceProp_t;
+
+typedef struct cudart_handle {
+  void *handle;
+  uint16_t verbose;
+  cudartReturn_t (*cudaSetDevice)(int device);
+  cudartReturn_t (*cudaDeviceSynchronize)(void);
+  cudartReturn_t (*cudaDeviceReset)(void);
+  cudartReturn_t (*cudaMemGetInfo)(size_t *, size_t *);
+  cudartReturn_t (*cudaGetDeviceCount)(int *);
+  cudartReturn_t (*cudaDeviceGetAttribute)(int* value, cudartDeviceAttr_t attr, int device);
+  cudartReturn_t (*cudaDriverGetVersion) (int *driverVersion);
+  cudartReturn_t (*cudaGetDeviceProperties) (cudaDeviceProp_t* prop, int device);
+} cudart_handle_t;
+
+typedef struct cudart_init_resp {
+  char *err;  // If err is non-null handle is invalid
+  cudart_handle_t ch;
+  int num_devices;
+} cudart_init_resp_t;
+
+void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp);
+void cudart_check_vram(cudart_handle_t ch, int device_id, mem_info_t *resp);
+void cudart_release(cudart_handle_t ch);
+
+#endif  // __GPU_INFO_CUDART_H__
+#endif  // __APPLE__

gpu/gpu_info_darwin.h

@@ -0,0 +1,4 @@
+#import <Metal/Metal.h>
+#include <stdint.h>
+uint64_t getRecommendedMaxVRAM();
+uint64_t getPhysicalMemory();

gpu/gpu_info_darwin.m

@@ -0,0 +1,13 @@
+// go:build darwin
+#include "gpu_info_darwin.h"
+
+uint64_t getRecommendedMaxVRAM() {
+  id<MTLDevice> device = MTLCreateSystemDefaultDevice();
+  uint64_t result = device.recommendedMaxWorkingSetSize;
+  CFRelease(device);
+  return result;
+}
+
+uint64_t getPhysicalMemory() {
+  return [[NSProcessInfo processInfo] physicalMemory];
+}

gpu/gpu_info_rocm.c

@@ -1,198 +0,0 @@
-#ifndef __APPLE__
-
-#include "gpu_info_rocm.h"
-
-#include <string.h>
-
-void rocm_init(char *rocm_lib_path, rocm_init_resp_t *resp) {
-  rsmi_status_t ret;
-  resp->err = NULL;
-  const int buflen = 256;
-  char buf[buflen + 1];
-  int i;
-  struct lookup {
-    char *s;
-    void **p;
-  } l[] = {
-      {"rsmi_init", (void *)&resp->rh.rsmi_init},
-      {"rsmi_shut_down", (void *)&resp->rh.rsmi_shut_down},
-      {"rsmi_dev_memory_total_get", (void *)&resp->rh.rsmi_dev_memory_total_get},
-      {"rsmi_dev_memory_usage_get", (void *)&resp->rh.rsmi_dev_memory_usage_get},
-      {"rsmi_version_get", (void *)&resp->rh.rsmi_version_get},
-      {"rsmi_num_monitor_devices", (void*)&resp->rh.rsmi_num_monitor_devices},
-      {"rsmi_dev_id_get", (void*)&resp->rh.rsmi_dev_id_get},
-      {"rsmi_dev_name_get", (void *)&resp->rh.rsmi_dev_name_get},
-      {"rsmi_dev_brand_get", (void *)&resp->rh.rsmi_dev_brand_get},
-      {"rsmi_dev_vendor_name_get", (void *)&resp->rh.rsmi_dev_vendor_name_get},
-      {"rsmi_dev_vram_vendor_get", (void *)&resp->rh.rsmi_dev_vram_vendor_get},
-      {"rsmi_dev_serial_number_get", (void *)&resp->rh.rsmi_dev_serial_number_get},
-      {"rsmi_dev_subsystem_name_get", (void *)&resp->rh.rsmi_dev_subsystem_name_get},
-      {"rsmi_dev_vbios_version_get", (void *)&resp->rh.rsmi_dev_vbios_version_get},
-      {NULL, NULL},
-  };
-
-  resp->rh.handle = LOAD_LIBRARY(rocm_lib_path, RTLD_LAZY);
-  if (!resp->rh.handle) {
-    char *msg = LOAD_ERR();
-    snprintf(buf, buflen,
-             "Unable to load %s library to query for Radeon GPUs: %s\n",
-             rocm_lib_path, msg);
-    free(msg);
-    resp->err = strdup(buf);
-    return;
-  }
-
-  // TODO once we've squashed the remaining corner cases remove this log
-  LOG(resp->rh.verbose, "wiring rocm management library functions in %s\n", rocm_lib_path);
-
-  for (i = 0; l[i].s != NULL; i++) {
-    // TODO once we've squashed the remaining corner cases remove this log
-    LOG(resp->rh.verbose, "dlsym: %s\n", l[i].s);
-
-    *l[i].p = LOAD_SYMBOL(resp->rh.handle, l[i].s);
-    if (!l[i].p) {
-      resp->rh.handle = NULL;
-      char *msg = LOAD_ERR();
-      LOG(resp->rh.verbose, "dlerr: %s\n", msg);
-      UNLOAD_LIBRARY(resp->rh.handle);
-      snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
-               msg);
-      free(msg);
-      resp->err = strdup(buf);
-      return;
-    }
-  }
-
-  ret = (*resp->rh.rsmi_init)(0);
-  if (ret != RSMI_STATUS_SUCCESS) {
-    LOG(resp->rh.verbose, "rsmi_init err: %d\n", ret);
-    UNLOAD_LIBRARY(resp->rh.handle);
-    resp->rh.handle = NULL;
-    snprintf(buf, buflen, "rocm vram init failure: %d", ret);
-    resp->err = strdup(buf);
-  }
-
-  return;
-}
-
-void rocm_check_vram(rocm_handle_t h, mem_info_t *resp) {
-  resp->err = NULL;
-  resp->igpu_index = -1;
-  uint64_t totalMem = 0;
-  uint64_t usedMem = 0;
-  rsmi_status_t ret;
-  const int buflen = 256;
-  char buf[buflen + 1];
-  int i;
-
-  if (h.handle == NULL) {
-    resp->err = strdup("rocm handle not initialized");
-    return;
-  }
-
-  ret = (*h.rsmi_num_monitor_devices)(&resp->count);
-  if (ret != RSMI_STATUS_SUCCESS) {
-    snprintf(buf, buflen, "unable to get device count: %d", ret);
-    resp->err = strdup(buf);
-    return;
-  }
-  LOG(h.verbose, "discovered %d ROCm GPU Devices\n", resp->count);
-
-  resp->total = 0;
-  resp->free = 0;
-  for (i = 0; i < resp->count; i++) {
-    if (h.verbose) {
-      // When in verbose mode, report more information about
-      // the card we discover, but don't fail on error
-      ret = (*h.rsmi_dev_name_get)(i, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "rsmi_dev_name_get failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] ROCm device name: %s\n", i, buf);
-      }
-      ret = (*h.rsmi_dev_brand_get)(i, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "rsmi_dev_brand_get failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] ROCm brand: %s\n", i, buf);
-      }
-      ret = (*h.rsmi_dev_vendor_name_get)(i, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "rsmi_dev_vendor_name_get failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] ROCm vendor: %s\n", i, buf);
-      }
-      ret = (*h.rsmi_dev_vram_vendor_get)(i, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "rsmi_dev_vram_vendor_get failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] ROCm VRAM vendor: %s\n", i, buf);
-      }
-      ret = (*h.rsmi_dev_serial_number_get)(i, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "rsmi_dev_serial_number_get failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] ROCm S/N: %s\n", i, buf);
-      }
-      ret = (*h.rsmi_dev_subsystem_name_get)(i, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "rsmi_dev_subsystem_name_get failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] ROCm subsystem name: %s\n", i, buf);
-      }
-      ret = (*h.rsmi_dev_vbios_version_get)(i, buf, buflen);
-      if (ret != RSMI_STATUS_SUCCESS) {
-        LOG(h.verbose, "rsmi_dev_vbios_version_get failed: %d\n", ret);
-      } else {
-        LOG(h.verbose, "[%d] ROCm vbios version: %s\n", i, buf);
-      }
-    }
-
-    // Get total memory - used memory for available memory
-    ret = (*h.rsmi_dev_memory_total_get)(i, RSMI_MEM_TYPE_VRAM, &totalMem);
-    if (ret != RSMI_STATUS_SUCCESS) {
-      snprintf(buf, buflen, "rocm total mem lookup failure: %d", ret);
-      resp->err = strdup(buf);
-      return;
-    }
-    ret = (*h.rsmi_dev_memory_usage_get)(i, RSMI_MEM_TYPE_VRAM, &usedMem);
-    if (ret != RSMI_STATUS_SUCCESS) {
-      snprintf(buf, buflen, "rocm usage mem lookup failure: %d", ret);
-      resp->err = strdup(buf);
-      return;
-    }
-    LOG(h.verbose, "[%d] ROCm totalMem %ld\n", i, totalMem);
-    LOG(h.verbose, "[%d] ROCm usedMem %ld\n", i, usedMem);
-    if (totalMem < 1024 * 1024 * 1024) {
-      // Do not add up integrated GPU memory capacity, it's a bogus 512M, and actually uses system memory
-      LOG(h.verbose, "[%d] ROCm integrated GPU\n", i);
-      resp->igpu_index = i;
-    } else {
-      resp->total += totalMem;
-      resp->free += totalMem - usedMem;
-    }
-  }
-}
-
-void rocm_get_version(rocm_handle_t h, rocm_version_resp_t *resp) {
-  const int buflen = 256;
-  char buf[buflen + 1];
-  if (h.handle == NULL) {
-    resp->str = strdup("rocm handle not initialized");
-    resp->status = 1;
-    return;
-  }
-  rsmi_version_t ver;
-  rsmi_status_t ret;
-  ret = h.rsmi_version_get(&ver);
-  if (ret != RSMI_STATUS_SUCCESS) {
-    snprintf(buf, buflen, "unexpected response on version lookup %d", ret);
-    resp->status = 1;
-  } else {
-    snprintf(buf, buflen, "%d", ver.major);
-    resp->status = 0;
-  }
-  resp->str = strdup(buf);
-}
-
-#endif  // __APPLE__

gpu/gpu_info_rocm.h

@@ -1,59 +0,0 @@
-#ifndef __APPLE__
-#ifndef __GPU_INFO_ROCM_H__
-#define __GPU_INFO_ROCM_H__
-#include "gpu_info.h"
-
-// Just enough typedef's to dlopen/dlsym for memory information
-typedef enum rsmi_status_return {
-  RSMI_STATUS_SUCCESS = 0,
-  // Other values omitted for now...
-} rsmi_status_t;
-
-typedef enum rsmi_memory_type {
-  RSMI_MEM_TYPE_VRAM = 0,
-  RSMI_MEM_TYPE_VIS_VRAM,
-  RSMI_MEM_TYPE_GTT,
-} rsmi_memory_type_t;
-
- typedef struct {
-     uint32_t major;     
-     uint32_t minor;     
-     uint32_t patch;     
-     const char *build;  
- } rsmi_version_t;
-
-typedef struct rocm_handle {
-  void *handle;
-  uint16_t verbose;
-  rsmi_status_t (*rsmi_init)(uint64_t);
-  rsmi_status_t (*rsmi_shut_down)(void);
-  rsmi_status_t (*rsmi_dev_memory_total_get)(uint32_t, rsmi_memory_type_t, uint64_t *);
-  rsmi_status_t (*rsmi_dev_memory_usage_get)(uint32_t, rsmi_memory_type_t, uint64_t *);
-  rsmi_status_t (*rsmi_version_get) (rsmi_version_t *version);
-  rsmi_status_t (*rsmi_num_monitor_devices) (uint32_t *);
-  rsmi_status_t (*rsmi_dev_id_get)(uint32_t, uint16_t *);
-  rsmi_status_t (*rsmi_dev_name_get) (uint32_t,char *,size_t);
-  rsmi_status_t (*rsmi_dev_brand_get) (uint32_t, char *, uint32_t);		
-  rsmi_status_t (*rsmi_dev_vendor_name_get) (uint32_t, char *, uint32_t);		
-  rsmi_status_t (*rsmi_dev_vram_vendor_get) (uint32_t, char *, uint32_t);		
-  rsmi_status_t (*rsmi_dev_serial_number_get) (uint32_t, char *, uint32_t);		
-  rsmi_status_t (*rsmi_dev_subsystem_name_get) (uint32_t, char *, uint32_t);		
-  rsmi_status_t (*rsmi_dev_vbios_version_get) (uint32_t, char *, uint32_t);		
-} rocm_handle_t;
-
-typedef struct rocm_init_resp {
-  char *err;  // If err is non-null handle is invalid
-  rocm_handle_t rh;
-} rocm_init_resp_t;
-
-typedef struct rocm_version_resp {
-  rsmi_status_t status;
-  char *str; // Contains version or error string if status != 0 
-} rocm_version_resp_t;
-
-void rocm_init(char *rocm_lib_path, rocm_init_resp_t *resp);
-void rocm_check_vram(rocm_handle_t rh, mem_info_t *resp);
-void rocm_get_version(rocm_handle_t rh, rocm_version_resp_t *resp);
-
-#endif  // __GPU_INFO_ROCM_H__
-#endif  // __APPLE__

gpu/gpu_test.go

@@ -9,23 +9,16 @@ import (
 
 func TestBasicGetGPUInfo(t *testing.T) {
 	info := GetGPUInfo()
-	assert.Contains(t, "cuda rocm cpu metal", info.Library)
-
-	switch runtime.GOOS {
-	case "darwin":
-		// TODO - remove this once MacOS returns some size for CPU
-		return
-	case "linux", "windows":
-		assert.Greater(t, info.TotalMemory, uint64(0))
-		assert.Greater(t, info.FreeMemory, uint64(0))
-		assert.Greater(t, info.DeviceCount, uint32(0))
-	default:
-		return
+	assert.Greater(t, len(info), 0)
+	assert.Contains(t, "cuda rocm cpu metal", info[0].Library)
+	if info[0].Library != "cpu" {
+		assert.Greater(t, info[0].TotalMemory, uint64(0))
+		assert.Greater(t, info[0].FreeMemory, uint64(0))
 	}
 }
 
 func TestCPUMemInfo(t *testing.T) {
-	info, err := getCPUMem()
+	info, err := GetCPUMem()
 	assert.NoError(t, err)
 	switch runtime.GOOS {
 	case "darwin":

gpu/types.go

@@ -3,7 +3,6 @@ package gpu
 type memInfo struct {
 	TotalMemory uint64 `json:"total_memory,omitempty"`
 	FreeMemory  uint64 `json:"free_memory,omitempty"`
-	DeviceCount uint32 `json:"device_count,omitempty"`
 }
 
 // Beginning of an `ollama info` command
@@ -14,11 +13,52 @@ type GpuInfo struct {
 	// Optional variant to select (e.g. versions, cpu feature flags)
 	Variant string `json:"variant,omitempty"`
 
-	// TODO add other useful attributes about the card here for discovery information
+	// MinimumMemory represents the minimum memory required to use the GPU
+	MinimumMemory uint64 `json:"-"`
+
+	// Any extra PATH/LD_LIBRARY_PATH dependencies required for the Library to operate properly
+	DependencyPath string `json:"lib_path,omitempty"`
+
+	// GPU information
+	ID    string `json:"gpu_id"`          // string to use for selection of this specific GPU
+	Name  string `json:"name"`            // user friendly name if available
+	Major int    `json:"major,omitempty"` // Major compatibility version (CC or gfx)
+	Minor int    `json:"minor,omitempty"` // Minor compatibility version (CC or gfx)
+	Patch int    `json:"patch,omitempty"` // Patch compatibility only matters on AMD
+
+	// TODO other performance capability info to help in scheduling decisions
 }
 
-type Version struct {
-	Major uint
-	Minor uint
-	Patch uint
+type GpuInfoList []GpuInfo
+
+// Split up the set of gpu info's by Library and variant
+func (l GpuInfoList) ByLibrary() []GpuInfoList {
+	resp := []GpuInfoList{}
+	libs := []string{}
+	for _, info := range l {
+		found := false
+		requested := info.Library
+		if info.Variant != "" {
+			requested += "_" + info.Variant
+		}
+		for i, lib := range libs {
+			if lib == requested {
+				resp[i] = append(resp[i], info)
+				found = true
+				break
+			}
+		}
+		if !found {
+			libs = append(libs, info.Library)
+			resp = append(resp, []GpuInfo{info})
+		}
+	}
+	return resp
 }
+
+// Sort by Free Space
+type ByFreeMemory []GpuInfo
+
+func (a ByFreeMemory) Len() int           { return len(a) }
+func (a ByFreeMemory) Swap(i, j int)      { a[i], a[j] = a[j], a[i] }
+func (a ByFreeMemory) Less(i, j int) bool { return a[i].FreeMemory < a[j].FreeMemory }

integration/README.md

@@ -0,0 +1,11 @@
+# Integration Tests
+
+This directory contains integration tests to exercise Ollama end-to-end to verify behavior
+
+By default, these tests are disabled so `go test ./...` will exercise only unit tests.  To run integration tests you must pass the integration tag.  `go test -tags=integration ./...`
+
+
+The integration tests have 2 modes of operating.
+
+1. By default, they will start the server on a random port, run the tests, and then shutdown the server.
+2. If `OLLAMA_TEST_EXISTING` is set to a non-empty string, the tests will run against an existing running server, which can be remote

integration/basic_test.go

@@ -0,0 +1,70 @@
+//go:build integration
+
+package integration
+
+import (
+	"context"
+	"log/slog"
+	"os"
+	"runtime"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+	"github.com/stretchr/testify/require"
+)
+
+func TestOrcaMiniBlueSky(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+	// Set up the test data
+	req := api.GenerateRequest{
+		Model:  "orca-mini",
+		Prompt: "why is the sky blue?",
+		Stream: &stream,
+		Options: map[string]interface{}{
+			"temperature": 0,
+			"seed":        123,
+		},
+	}
+	GenerateTestHelper(ctx, t, req, []string{"rayleigh", "scattering"})
+}
+
+func TestUnicodeModelDir(t *testing.T) {
+	// This is only useful for Windows with utf-16 characters, so skip this test for other platforms
+	if runtime.GOOS != "windows" {
+		t.Skip("Unicode test only applicable to windows")
+	}
+	// Only works for local testing
+	if os.Getenv("OLLAMA_TEST_EXISTING") != "" {
+		t.Skip("TestUnicodeModelDir only works for local testing, skipping")
+	}
+
+	modelDir, err := os.MkdirTemp("", "ollama_埃")
+	require.NoError(t, err)
+	defer os.RemoveAll(modelDir)
+	slog.Info("unicode", "OLLAMA_MODELS", modelDir)
+
+	oldModelsDir := os.Getenv("OLLAMA_MODELS")
+	if oldModelsDir == "" {
+		defer os.Unsetenv("OLLAMA_MODELS")
+	} else {
+		defer os.Setenv("OLLAMA_MODELS", oldModelsDir)
+	}
+	err = os.Setenv("OLLAMA_MODELS", modelDir)
+	require.NoError(t, err)
+
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+
+	req := api.GenerateRequest{
+		Model:  "orca-mini",
+		Prompt: "why is the sky blue?",
+		Stream: &stream,
+		Options: map[string]interface{}{
+			"temperature": 0,
+			"seed":        123,
+		},
+	}
+	GenerateTestHelper(ctx, t, req, []string{"rayleigh", "scattering"})
+}

integration/concurrency_test.go

@@ -0,0 +1,225 @@
+//go:build integration
+
+package integration
+
+import (
+	"context"
+	"log/slog"
+	"os"
+	"strconv"
+	"sync"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+	"github.com/stretchr/testify/require"
+)
+
+func TestMultiModelConcurrency(t *testing.T) {
+	var (
+		req = [2]api.GenerateRequest{
+			{
+				Model:  "orca-mini",
+				Prompt: "why is the ocean blue?",
+				Stream: &stream,
+				Options: map[string]interface{}{
+					"seed":        42,
+					"temperature": 0.0,
+				},
+			}, {
+				Model:  "tinydolphin",
+				Prompt: "what is the origin of the us thanksgiving holiday?",
+				Stream: &stream,
+				Options: map[string]interface{}{
+					"seed":        42,
+					"temperature": 0.0,
+				},
+			},
+		}
+		resp = [2][]string{
+			[]string{"sunlight"},
+			[]string{"england", "english", "massachusetts", "pilgrims"},
+		}
+	)
+	var wg sync.WaitGroup
+	wg.Add(len(req))
+	ctx, cancel := context.WithTimeout(context.Background(), time.Second*120)
+	defer cancel()
+	for i := 0; i < len(req); i++ {
+		go func(i int) {
+			defer wg.Done()
+			GenerateTestHelper(ctx, t, req[i], resp[i])
+		}(i)
+	}
+	wg.Wait()
+}
+
+func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 10*time.Minute) // GTX 750 2G card takes ~9 minutes
+	defer cancel()
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+
+	req, resp := GenerateRequests()
+	// Get the server running (if applicable) warm the model up with a single initial request
+	DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 5*time.Second)
+
+	var wg sync.WaitGroup
+	wg.Add(len(req))
+	for i := 0; i < len(req); i++ {
+		go func(i int) {
+			defer wg.Done()
+			for j := 0; j < 5; j++ {
+				slog.Info("Starting", "req", i, "iter", j)
+				// On slower GPUs it can take a while to process the 4 concurrent requests
+				// so we allow a much longer initial timeout
+				DoGenerate(ctx, t, client, req[i], resp[i], 90*time.Second, 5*time.Second)
+			}
+		}(i)
+	}
+	wg.Wait()
+}
+
+// Stress the system if we know how much VRAM it has, and attempt to load more models than will fit
+func TestMultiModelStress(t *testing.T) {
+	vram := os.Getenv("OLLAMA_MAX_VRAM")
+	if vram == "" {
+		t.Skip("OLLAMA_MAX_VRAM not specified, can't pick the right models for the stress test")
+	}
+	max, err := strconv.ParseUint(vram, 10, 64)
+	require.NoError(t, err)
+	const MB = uint64(1024 * 1024)
+	type model struct {
+		name string
+		size uint64 // Approximate amount of VRAM they typically use when fully loaded in VRAM
+	}
+
+	smallModels := []model{
+		{
+			name: "orca-mini",
+			size: 2992 * MB,
+		},
+		{
+			name: "phi",
+			size: 2616 * MB,
+		},
+		{
+			name: "gemma:2b",
+			size: 2364 * MB,
+		},
+		{
+			name: "stable-code:3b",
+			size: 2608 * MB,
+		},
+		{
+			name: "starcoder2:3b",
+			size: 2166 * MB,
+		},
+	}
+	mediumModels := []model{
+		{
+			name: "llama2",
+			size: 5118 * MB,
+		},
+		{
+			name: "mistral",
+			size: 4620 * MB,
+		},
+		{
+			name: "orca-mini:7b",
+			size: 5118 * MB,
+		},
+		{
+			name: "dolphin-mistral",
+			size: 4620 * MB,
+		},
+		{
+			name: "gemma:7b",
+			size: 5000 * MB,
+		},
+		// TODO - uncomment this once #3565 is merged and this is rebased on it
+		// {
+		// 	name: "codellama:7b",
+		// 	size: 5118 * MB,
+		// },
+	}
+
+	// These seem to be too slow to be useful...
+	// largeModels := []model{
+	// 	{
+	// 		name: "llama2:13b",
+	// 		size: 7400 * MB,
+	// 	},
+	// 	{
+	// 		name: "codellama:13b",
+	// 		size: 7400 * MB,
+	// 	},
+	// 	{
+	// 		name: "orca-mini:13b",
+	// 		size: 7400 * MB,
+	// 	},
+	// 	{
+	// 		name: "gemma:7b",
+	// 		size: 5000 * MB,
+	// 	},
+	// 	{
+	// 		name: "starcoder2:15b",
+	// 		size: 9100 * MB,
+	// 	},
+	// }
+
+	var chosenModels []model
+	switch {
+	case max < 10000*MB:
+		slog.Info("selecting small models")
+		chosenModels = smallModels
+	// case max < 30000*MB:
+	default:
+		slog.Info("selecting medium models")
+		chosenModels = mediumModels
+		// default:
+		// 	slog.Info("selecting large models")
+		// 	chosenModels = largModels
+	}
+
+	req, resp := GenerateRequests()
+
+	for i := range req {
+		if i > len(chosenModels) {
+			break
+		}
+		req[i].Model = chosenModels[i].name
+	}
+
+	ctx, cancel := context.WithTimeout(context.Background(), 15*time.Minute) // TODO baseline -- 10m too short
+	defer cancel()
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+
+	// Make sure all the models are pulled before we get started
+	for _, r := range req {
+		require.NoError(t, PullIfMissing(ctx, client, r.Model))
+	}
+
+	var wg sync.WaitGroup
+	consumed := uint64(256 * MB) // Assume some baseline usage
+	for i := 0; i < len(req); i++ {
+		// Always get at least 2 models, but dont' overshoot VRAM too much or we'll take too long
+		if i > 1 && consumed > max {
+			slog.Info("achieved target vram exhaustion", "count", i, "vramMB", max/1024/1024, "modelsMB", consumed/1024/1024)
+			break
+		}
+		consumed += chosenModels[i].size
+		slog.Info("target vram", "count", i, "vramMB", max/1024/1024, "modelsMB", consumed/1024/1024)
+
+		wg.Add(1)
+		go func(i int) {
+			defer wg.Done()
+			for j := 0; j < 3; j++ {
+				slog.Info("Starting", "req", i, "iter", j, "model", req[i].Model)
+				DoGenerate(ctx, t, client, req[i], resp[i], 90*time.Second, 5*time.Second)
+			}
+		}(i)
+	}
+	wg.Wait()
+}

integration/context_test.go

@@ -0,0 +1,28 @@
+//go:build integration
+
+package integration
+
+import (
+	"context"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+)
+
+func TestContextExhaustion(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute) // TODO maybe shorter?
+	defer cancel()
+	// Set up the test data
+	req := api.GenerateRequest{
+		Model:  "llama2",
+		Prompt: "Write me a story with a ton of emojis?",
+		Stream: &stream,
+		Options: map[string]interface{}{
+			"temperature": 0,
+			"seed":        123,
+			"num_ctx":     128,
+		},
+	}
+	GenerateTestHelper(ctx, t, req, []string{"once", "upon", "lived"})
+}

integration/embedding_test.go

@@ -0,0 +1,64 @@
+//go:build integration
+
+package integration
+
+import (
+	"context"
+	"net/http"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+)
+
+func TestAllMiniLMEmbedding(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+
+	req := api.EmbeddingRequest{
+		Model:  "all-minilm",
+		Prompt: "why is the sky blue?",
+		Options: map[string]interface{}{
+			"temperature": 0,
+			"seed":        123,
+		},
+	}
+
+	res := EmbeddingTestHelper(ctx, t, &http.Client{}, req)
+
+	if len(res.Embedding) != 384 {
+		t.Fatalf("Expected 384 floats to be returned, got %v", len(res.Embedding))
+	}
+
+	if res.Embedding[0] != 0.146763876080513 {
+		t.Fatalf("Expected first embedding float to be 0.146763876080513, got %v", res.Embedding[0])
+	}
+}
+
+func TestAllMiniLMEmbeddings(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+
+	req := api.EmbeddingRequest{
+		Model:   "all-minilm",
+		Prompts: []string{"why is the sky blue?", "why is the sky blue?"},
+		Options: map[string]interface{}{
+			"temperature": 0,
+			"seed":        123,
+		},
+	}
+
+	res := EmbeddingTestHelper(ctx, t, &http.Client{}, req)
+
+	if len(res.Embeddings) != 2 {
+		t.Fatal("Expected 2 embeddings to be returned")
+	}
+
+	if len(res.Embeddings[0]) != 384 {
+		t.Fatalf("Expected first embedding to have 384 floats, got %v", len(res.Embeddings[0]))
+	}
+
+	if res.Embeddings[0][0] != 0.146763876080513 && res.Embeddings[1][0] != 0.146763876080513 {
+		t.Fatalf("Expected first embedding floats to be 0.146763876080513, got %v, %v", res.Embeddings[0][0], res.Embeddings[1][0])
+	}
+}

integration/llm_image_test.go

@@ -1,49 +1,38 @@
 //go:build integration
 
-package server
+package integration
 
 import (
 	"context"
 	"encoding/base64"
-	"log"
-	"os"
-	"strings"
 	"testing"
 	"time"
 
-	"github.com/jmorganca/ollama/api"
-	"github.com/jmorganca/ollama/llm"
-	"github.com/stretchr/testify/assert"
+	"github.com/ollama/ollama/api"
 	"github.com/stretchr/testify/require"
 )
 
 func TestIntegrationMultimodal(t *testing.T) {
-	SkipIFNoTestData(t)
 	image, err := base64.StdEncoding.DecodeString(imageEncoding)
 	require.NoError(t, err)
 	req := api.GenerateRequest{
-		Model:   "llava:7b",
-		Prompt:  "what does the text in this image say?",
-		Options: map[string]interface{}{},
+		Model:  "llava:7b",
+		Prompt: "what does the text in this image say?",
+		Stream: &stream,
+		Options: map[string]interface{}{
+			"seed":        42,
+			"temperature": 0.0,
+		},
 		Images: []api.ImageData{
 			image,
 		},
 	}
-	resp := "the ollamas"
-	workDir, err := os.MkdirTemp("", "ollama")
-	require.NoError(t, err)
-	defer os.RemoveAll(workDir)
-	require.NoError(t, llm.Init(workDir))
-	ctx, cancel := context.WithTimeout(context.Background(), time.Second*60)
+
+	// Note: sometimes it returns "the ollamas" sometimes "the ollams"
+	resp := "the ollam"
+	ctx, cancel := context.WithTimeout(context.Background(), 3*time.Minute)
 	defer cancel()
-	opts := api.DefaultOptions()
-	opts.Seed = 42
-	opts.Temperature = 0.0
-	model, llmRunner := PrepareModelForPrompts(t, req.Model, opts)
-	defer llmRunner.Close()
-	response := OneShotPromptResponse(t, ctx, req, model, llmRunner)
-	log.Print(response)
-	assert.Contains(t, strings.ToLower(response), resp)
+	GenerateTestHelper(ctx, t, req, []string{resp})
 }
 
 const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb