merge main

.devcontainer/Dockerfile

@@ -1,4 +1,4 @@
-ARG BASEIMAGE=mcr.microsoft.com/devcontainers/typescript-node:22@sha256:9791f4aa527774bc370c6bd2f6705ce5a686f1e6f204badd8dfaacce28c631ae
+ARG BASEIMAGE=mcr.microsoft.com/devcontainers/typescript-node:22@sha256:2ef23730ec68d8511ec8e6e0b82550ca728b256805d81f60ed890f3bfb21cfb9
 FROM ${BASEIMAGE}
 
 # Flutter SDK

.github/workflows/build-mobile.yml

@@ -22,9 +22,9 @@ jobs:
       should_run: ${{ steps.found_paths.outputs.mobile == 'true' || steps.should_force.outputs.should_force == 'true' }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - id: found_paths
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@de90cc6fb38fc0963ad72b210f1f284cd68cea36 # v3
         with:
           filters: |
             mobile:
@@ -51,18 +51,18 @@ jobs:
           ref="${input_ref:-$github_ref}"
           echo "ref=$ref" >> $GITHUB_OUTPUT
 
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
         with:
           ref: ${{ steps.get-ref.outputs.ref }}
 
-      - uses: actions/setup-java@v4
+      - uses: actions/setup-java@3a4f6e1af504cf6a31855fa899c6aa5355ba6c12 # v4
         with:
           distribution: 'zulu'
           java-version: '17'
           cache: 'gradle'
 
       - name: Setup Flutter SDK
-        uses: subosito/flutter-action@v2
+        uses: subosito/flutter-action@44ac965b96f18d999802d4b807e3256d5a3f9fa1 # v2
         with:
           channel: 'stable'
           flutter-version-file: ./mobile/pubspec.yaml
@@ -89,7 +89,7 @@ jobs:
           flutter build apk --release --split-per-abi --target-platform android-arm,android-arm64,android-x64
 
       - name: Publish Android Artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@4cec3d8aa04e39d1a68397de0c4cd6fb9dce8ec1 # v4
         with:
           name: release-apk-signed
           path: mobile/build/app/outputs/flutter-apk/*.apk

.github/workflows/cache-cleanup.yml

@@ -14,7 +14,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Cleanup
         run: |

.github/workflows/cli.yml

@@ -29,9 +29,9 @@ jobs:
         working-directory: ./cli
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       # Setup .npmrc file to publish to npm
-      - uses: actions/setup-node@v4
+      - uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './cli/.nvmrc'
           registry-url: 'https://registry.npmjs.org'
@@ -53,16 +53,16 @@ jobs:
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Set up QEMU
-        uses: docker/setup-qemu-action@v3.6.0
+        uses: docker/setup-qemu-action@29109295f81e9208d7d86ff1c6c12d2833863392 # v3.6.0
 
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3.10.0
+        uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 # v3.10.0
 
       - name: Login to GitHub Container Registry
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         if: ${{ !github.event.pull_request.head.repo.fork }}
         with:
           registry: ghcr.io
@@ -77,7 +77,7 @@ jobs:
 
       - name: Generate docker image tags
         id: metadata
-        uses: docker/metadata-action@v5
+        uses: docker/metadata-action@902fa8ec7d6ecbf8d84d538b9b233a880e428804 # v5
         with:
           flavor: |
             latest=false
@@ -88,7 +88,7 @@ jobs:
             type=raw,value=latest,enable=${{ github.event_name == 'release' }}
 
       - name: Build and push image
-        uses: docker/build-push-action@v6.15.0
+        uses: docker/build-push-action@471d1dc4e07e5cdedd4c2171150001c434f0b7a4 # v6.15.0
         with:
           file: cli/Dockerfile
           platforms: linux/amd64,linux/arm64

.github/workflows/codeql-analysis.yml

@@ -42,11 +42,11 @@ jobs:
 
     steps:
     - name: Checkout repository
-      uses: actions/checkout@v4
+      uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v3
+      uses: github/codeql-action/init@6bb031afdd8eb862ea3fc1848194185e076637e5 # v3
       with:
         languages: ${{ matrix.language }}
         # If you wish to specify custom queries, you can do so here or in a config file.
@@ -60,7 +60,7 @@ jobs:
     # Autobuild attempts to build any compiled languages  (C/C++, C#, or Java).
     # If this step fails, then you should remove it and run the build manually (see below)
     - name: Autobuild
-      uses: github/codeql-action/autobuild@v3
+      uses: github/codeql-action/autobuild@6bb031afdd8eb862ea3fc1848194185e076637e5 # v3
 
     # ℹ️ Command-line programs to run using the OS shell.
     # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
@@ -73,6 +73,6 @@ jobs:
     #   ./location_of_script_within_repo/buildscript.sh
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v3
+      uses: github/codeql-action/analyze@6bb031afdd8eb862ea3fc1848194185e076637e5 # v3
       with:
         category: "/language:${{matrix.language}}"

.github/workflows/docker.yml

@@ -23,9 +23,9 @@ jobs:
       should_run_ml: ${{ steps.found_paths.outputs.machine-learning == 'true' || steps.should_force.outputs.should_force == 'true' }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - id: found_paths
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@de90cc6fb38fc0963ad72b210f1f284cd68cea36 # v3
         with:
           filters: |
             server:
@@ -49,7 +49,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        suffix: ["", "-cuda", "-openvino", "-armnn"]
+        suffix: ['', '-cuda', '-rocm', '-openvino', '-armnn', '-rknn']
     steps:
       - name: Login to GitHub Container Registry
         uses: docker/login-action@v3
@@ -66,6 +66,21 @@ jobs:
           TAG_COMMIT=commit-${{ github.event_name != 'pull_request' && github.sha || github.event.pull_request.head.sha }}${{ matrix.suffix }}
           docker buildx imagetools create -t $REGISTRY_NAME/$REPOSITORY:$TAG_PR $REGISTRY_NAME/$REPOSITORY:$TAG_OLD
           docker buildx imagetools create -t $REGISTRY_NAME/$REPOSITORY:$TAG_COMMIT $REGISTRY_NAME/$REPOSITORY:$TAG_OLD
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.repository_owner }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+      - name: Re-tag image
+        run: |
+          REGISTRY_NAME="ghcr.io"
+          REPOSITORY=${{ github.repository_owner }}/immich-machine-learning
+          TAG_OLD=main${{ matrix.suffix }}
+          TAG_PR=${{ github.event.number == 0 && github.ref_name ||  format('pr-{0}', github.event.number)  }}${{ matrix.suffix }}
+          TAG_COMMIT=commit-${{ github.event_name != 'pull_request' && github.sha || github.event.pull_request.head.sha }}${{ matrix.suffix }}
+          docker buildx imagetools create -t $REGISTRY_NAME/$REPOSITORY:$TAG_PR $REGISTRY_NAME/$REPOSITORY:$TAG_OLD
+          docker buildx imagetools create -t $REGISTRY_NAME/$REPOSITORY:$TAG_COMMIT $REGISTRY_NAME/$REPOSITORY:$TAG_OLD
 
   retag_server:
     name: Re-Tag Server
@@ -74,10 +89,10 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        suffix: [""]
+        suffix: ['']
     steps:
       - name: Login to GitHub Container Registry
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         with:
           registry: ghcr.io
           username: ${{ github.repository_owner }}
@@ -120,6 +135,11 @@ jobs:
             device: cuda
             suffix: -cuda
 
+          - platform: linux/amd64
+            runner: mich
+            device: rocm
+            suffix: -rocm
+
           - platform: linux/amd64
             runner: ubuntu-latest
             device: openvino
@@ -130,6 +150,11 @@ jobs:
             device: armnn
             suffix: -armnn
 
+          - platform: linux/arm64
+            runner: ubuntu-24.04-arm
+            device: rknn
+            suffix: -rknn
+
     steps:
       - name: Prepare
         run: |
@@ -137,13 +162,13 @@ jobs:
           echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3.10.0
+        uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 # v3.10.0
 
       - name: Login to GitHub Container Registry
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         if: ${{ !github.event.pull_request.head.repo.fork }}
         with:
           registry: ghcr.io
@@ -170,7 +195,7 @@ jobs:
 
       - name: Build and push image
         id: build
-        uses: docker/build-push-action@v6.15.0
+        uses: docker/build-push-action@471d1dc4e07e5cdedd4c2171150001c434f0b7a4 # v6.15.0
         with:
           context: ${{ env.context }}
           file: ${{ env.file }}
@@ -195,7 +220,7 @@ jobs:
           touch "${{ runner.temp }}/digests/${digest#sha256:}"
 
       - name: Upload digest
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@4cec3d8aa04e39d1a68397de0c4cd6fb9dce8ec1 # v4
         with:
           name: ml-digests-${{ matrix.device }}-${{ env.PLATFORM_PAIR }}
           path: ${{ runner.temp }}/digests/*
@@ -215,15 +240,19 @@ jobs:
           - device: cpu
           - device: cuda
             suffix: -cuda
+          - device: rocm
+            suffix: -rocm
           - device: openvino
             suffix: -openvino
           - device: armnn
             suffix: -armnn
+          - device: rknn
+            suffix: -rknn
     needs:
       - build_and_push_ml
     steps:
       - name: Download digests
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@cc203385981b70ca67e1cc392babf9cc229d5806 # v4
         with:
           path: ${{ runner.temp }}/digests
           pattern: ml-digests-${{ matrix.device }}-*
@@ -231,26 +260,26 @@ jobs:
 
       - name: Login to Docker Hub
         if: ${{ github.event_name == 'release' }}
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         with:
           username: ${{ secrets.DOCKERHUB_USERNAME }}
           password: ${{ secrets.DOCKERHUB_TOKEN }}
 
       - name: Login to GHCR
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         with:
           registry: ghcr.io
           username: ${{ github.repository_owner }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+        uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 # v3
 
       - name: Generate docker image tags
         id: meta
-        uses: docker/metadata-action@v5
+        uses: docker/metadata-action@902fa8ec7d6ecbf8d84d538b9b233a880e428804 # v5
         env:
-          DOCKER_METADATA_PR_HEAD_SHA: "true"
+          DOCKER_METADATA_PR_HEAD_SHA: 'true'
         with:
           flavor: |
             # Disable latest tag
@@ -301,13 +330,13 @@ jobs:
           echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+        uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 # v3
 
       - name: Login to GitHub Container Registry
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         if: ${{ !github.event.pull_request.head.repo.fork }}
         with:
           registry: ghcr.io
@@ -334,7 +363,7 @@ jobs:
 
       - name: Build and push image
         id: build
-        uses: docker/build-push-action@v6.15.0
+        uses: docker/build-push-action@471d1dc4e07e5cdedd4c2171150001c434f0b7a4 # v6.15.0
         with:
           context: ${{ env.context }}
           file: ${{ env.file }}
@@ -359,7 +388,7 @@ jobs:
           touch "${{ runner.temp }}/digests/${digest#sha256:}"
 
       - name: Upload digest
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@4cec3d8aa04e39d1a68397de0c4cd6fb9dce8ec1 # v4
         with:
           name: server-digests-${{ env.PLATFORM_PAIR }}
           path: ${{ runner.temp }}/digests/*
@@ -377,7 +406,7 @@ jobs:
       - build_and_push_server
     steps:
       - name: Download digests
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@cc203385981b70ca67e1cc392babf9cc229d5806 # v4
         with:
           path: ${{ runner.temp }}/digests
           pattern: server-digests-*
@@ -385,26 +414,26 @@ jobs:
 
       - name: Login to Docker Hub
         if: ${{ github.event_name == 'release' }}
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         with:
           username: ${{ secrets.DOCKERHUB_USERNAME }}
           password: ${{ secrets.DOCKERHUB_TOKEN }}
 
       - name: Login to GHCR
-        uses: docker/login-action@v3
+        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
         with:
           registry: ghcr.io
           username: ${{ github.repository_owner }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+        uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 # v3
 
       - name: Generate docker image tags
         id: meta
-        uses: docker/metadata-action@v5
+        uses: docker/metadata-action@902fa8ec7d6ecbf8d84d538b9b233a880e428804 # v5
         env:
-          DOCKER_METADATA_PR_HEAD_SHA: "true"
+          DOCKER_METADATA_PR_HEAD_SHA: 'true'
         with:
           flavor: |
             # Disable latest tag

.github/workflows/docs-build.yml

@@ -18,9 +18,9 @@ jobs:
       should_run: ${{ steps.found_paths.outputs.docs == 'true' ||  steps.should_force.outputs.should_force == 'true' }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - id: found_paths
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@de90cc6fb38fc0963ad72b210f1f284cd68cea36 # v3
         with:
           filters: |
             docs:
@@ -42,10 +42,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './docs/.nvmrc'
 
@@ -59,7 +59,7 @@ jobs:
         run: npm run build
 
       - name: Upload build output
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@4cec3d8aa04e39d1a68397de0c4cd6fb9dce8ec1 # v4
         with:
           name: docs-build-output
           path: docs/build/

.github/workflows/docs-deploy.yml

@@ -17,7 +17,7 @@ jobs:
         run: echo 'The triggering workflow did not succeed' && exit 1
       - name: Get artifact
         id: get-artifact
-        uses: actions/github-script@v7
+        uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7
         with:
           script: |
             let allArtifacts = await github.rest.actions.listWorkflowRunArtifacts({
@@ -35,7 +35,7 @@ jobs:
             return { found: true, id: matchArtifact.id };
       - name: Determine deploy parameters
         id: parameters
-        uses: actions/github-script@v7
+        uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7
         with:
           script: |
             const eventType = context.payload.workflow_run.event;
@@ -98,11 +98,11 @@ jobs:
     if: ${{ fromJson(needs.checks.outputs.artifact).found && fromJson(needs.checks.outputs.parameters).shouldDeploy }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Load parameters
         id: parameters
-        uses: actions/github-script@v7
+        uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7
         with:
           script: |
             const json = `${{ needs.checks.outputs.parameters }}`;
@@ -115,7 +115,7 @@ jobs:
           echo "Starting docs deployment for ${{ steps.parameters.outputs.event }} ${{ steps.parameters.outputs.name }}"
 
       - name: Download artifact
-        uses: actions/github-script@v7
+        uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7
         with:
           script: |
             let artifact = ${{ needs.checks.outputs.artifact }};
@@ -138,7 +138,7 @@ jobs:
           CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
           CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
           TF_STATE_POSTGRES_CONN_STR: ${{ secrets.TF_STATE_POSTGRES_CONN_STR }}
-        uses: gruntwork-io/terragrunt-action@v2
+        uses: gruntwork-io/terragrunt-action@9559e51d05873b0ea467c42bbabcb5c067642ccc # v2
         with:
           tg_version: "0.58.12"
           tofu_version: "1.7.1"
@@ -153,7 +153,7 @@ jobs:
           CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
           CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
           TF_STATE_POSTGRES_CONN_STR: ${{ secrets.TF_STATE_POSTGRES_CONN_STR }}
-        uses: gruntwork-io/terragrunt-action@v2
+        uses: gruntwork-io/terragrunt-action@9559e51d05873b0ea467c42bbabcb5c067642ccc # v2
         with:
           tg_version: "0.58.12"
           tofu_version: "1.7.1"
@@ -167,7 +167,7 @@ jobs:
           echo "output=$TG_OUT" >> $GITHUB_OUTPUT
 
       - name: Publish to Cloudflare Pages
-        uses: cloudflare/pages-action@v1
+        uses: cloudflare/pages-action@f0a1cd58cd66095dee69bfa18fa5efd1dde93bca # v1
         with:
           apiToken: ${{ secrets.CLOUDFLARE_API_TOKEN_PAGES_UPLOAD }}
           accountId: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
@@ -184,7 +184,7 @@ jobs:
           CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
           CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
           TF_STATE_POSTGRES_CONN_STR: ${{ secrets.TF_STATE_POSTGRES_CONN_STR }}
-        uses: gruntwork-io/terragrunt-action@v2
+        uses: gruntwork-io/terragrunt-action@9559e51d05873b0ea467c42bbabcb5c067642ccc # v2
         with:
           tg_version: '0.58.12'
           tofu_version: '1.7.1'
@@ -192,7 +192,7 @@ jobs:
           tg_command: 'apply'
 
       - name: Comment
-        uses: actions-cool/maintain-one-comment@v3
+        uses: actions-cool/maintain-one-comment@4b2dbf086015f892dcb5e8c1106f5fccd6c1476b # v3
         if: ${{ steps.parameters.outputs.event == 'pr' }}
         with:
           number: ${{ fromJson(needs.checks.outputs.parameters).pr_number }}

.github/workflows/docs-destroy.yml

@@ -9,7 +9,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Destroy Docs Subdomain
         env:
@@ -18,7 +18,7 @@ jobs:
           CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
           CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
           TF_STATE_POSTGRES_CONN_STR: ${{ secrets.TF_STATE_POSTGRES_CONN_STR }}
-        uses: gruntwork-io/terragrunt-action@v2
+        uses: gruntwork-io/terragrunt-action@9559e51d05873b0ea467c42bbabcb5c067642ccc # v2
         with:
           tg_version: "0.58.12"
           tofu_version: "1.7.1"
@@ -26,7 +26,7 @@ jobs:
           tg_command: "destroy -refresh=false"
 
       - name: Comment
-        uses: actions-cool/maintain-one-comment@v3
+        uses: actions-cool/maintain-one-comment@4b2dbf086015f892dcb5e8c1106f5fccd6c1476b # v3
         with:
           number: ${{ github.event.number }}
           delete: true

.github/workflows/fix-format.yml

@@ -13,19 +13,19 @@ jobs:
     steps:
       - name: Generate a token
         id: generate-token
-        uses: actions/create-github-app-token@v1
+        uses: actions/create-github-app-token@21cfef2b496dd8ef5b904c159339626a10ad380e # v1
         with:
           app-id: ${{ secrets.PUSH_O_MATIC_APP_ID }}
           private-key: ${{ secrets.PUSH_O_MATIC_APP_KEY }}
 
       - name: 'Checkout'
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
         with:
           ref: ${{ github.event.pull_request.head.ref }}
           token: ${{ steps.generate-token.outputs.token }}
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './server/.nvmrc'
 
@@ -33,13 +33,13 @@ jobs:
         run: make install-all && make format-all
 
       - name: Commit and push
-        uses: EndBug/add-and-commit@v9
+        uses: EndBug/add-and-commit@a94899bca583c204427a224a7af87c02f9b325d5 # v9
         with:
           default_author: github_actions
           message: 'chore: fix formatting'
 
       - name: Remove label
-        uses: actions/github-script@v7
+        uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7
         if: always()
         with:
           script: |

.github/workflows/pr-label-validation.yml

@@ -12,7 +12,7 @@ jobs:
       pull-requests: write
     steps:
       - name: Require PR to have a changelog label
-        uses: mheap/github-action-required-labels@v5
+        uses: mheap/github-action-required-labels@388fd6af37b34cdfe5a23b37060e763217e58b03 # v5
         with:
           mode: exactly
           count: 1

.github/workflows/pr-labeler.yml

@@ -9,4 +9,4 @@ jobs:
       pull-requests: write
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/labeler@v5
+    - uses: actions/labeler@8558fd74291d67161a8a78ce36a881fa63b766a9 # v5

.github/workflows/prepare-release.yml

@@ -31,25 +31,25 @@ jobs:
     steps:
       - name: Generate a token
         id: generate-token
-        uses: actions/create-github-app-token@v1
+        uses: actions/create-github-app-token@21cfef2b496dd8ef5b904c159339626a10ad380e # v1
         with:
           app-id: ${{ secrets.PUSH_O_MATIC_APP_ID }}
           private-key: ${{ secrets.PUSH_O_MATIC_APP_KEY }}
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
         with:
           token: ${{ steps.generate-token.outputs.token }}
 
       - name: Install uv
-        uses: astral-sh/setup-uv@v5
+        uses: astral-sh/setup-uv@f94ec6bedd8674c4426838e6b50417d36b6ab231 # v5
 
       - name: Bump version
         run: misc/release/pump-version.sh -s "${{ inputs.serverBump }}" -m "${{ inputs.mobileBump }}"
 
       - name: Commit and tag
         id: push-tag
-        uses: EndBug/add-and-commit@v9
+        uses: EndBug/add-and-commit@a94899bca583c204427a224a7af87c02f9b325d5 # v9
         with:
           default_author: github_actions
           message: 'chore: version ${{ env.IMMICH_VERSION }}'
@@ -70,23 +70,23 @@ jobs:
     steps:
       - name: Generate a token
         id: generate-token
-        uses: actions/create-github-app-token@v1
+        uses: actions/create-github-app-token@21cfef2b496dd8ef5b904c159339626a10ad380e # v1
         with:
           app-id: ${{ secrets.PUSH_O_MATIC_APP_ID }}
           private-key: ${{ secrets.PUSH_O_MATIC_APP_KEY }}
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
         with:
           token: ${{ steps.generate-token.outputs.token }}
 
       - name: Download APK
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@cc203385981b70ca67e1cc392babf9cc229d5806 # v4
         with:
           name: release-apk-signed
 
       - name: Create draft release
-        uses: softprops/action-gh-release@v2
+        uses: softprops/action-gh-release@c95fe1489396fe8a9eb87c0abf8aa5b2ef267fda # v2
         with:
           draft: true
           tag_name: ${{ env.IMMICH_VERSION }}

.github/workflows/preview-label.yaml

@@ -11,7 +11,7 @@ jobs:
     permissions:
       pull-requests: write
     steps:
-      - uses: mshick/add-pr-comment@v2
+      - uses: mshick/add-pr-comment@b8f338c590a895d50bcbfa6c5859251edc8952fc # v2
         with:
           message-id: "preview-status"
           message: "Deploying preview environment to https://pr-${{ github.event.pull_request.number }}.preview.internal.immich.cloud/"
@@ -22,7 +22,7 @@ jobs:
     permissions:
       pull-requests: write
     steps:
-      - uses: actions/github-script@v7
+      - uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7
         with:
           script: |
             github.rest.issues.removeLabel({

.github/workflows/sdk.yml

@@ -15,9 +15,9 @@ jobs:
       run:
         working-directory: ./open-api/typescript-sdk
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       # Setup .npmrc file to publish to npm
-      - uses: actions/setup-node@v4
+      - uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './open-api/typescript-sdk/.nvmrc'
           registry-url: 'https://registry.npmjs.org'

.github/workflows/static_analysis.yml

@@ -16,9 +16,9 @@ jobs:
       should_run: ${{ steps.found_paths.outputs.mobile == 'true' || steps.should_force.outputs.should_force == 'true' }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - id: found_paths
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@de90cc6fb38fc0963ad72b210f1f284cd68cea36 # v3
         with:
           filters: |
             mobile:
@@ -38,10 +38,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Flutter SDK
-        uses: subosito/flutter-action@v2
+        uses: subosito/flutter-action@44ac965b96f18d999802d4b807e3256d5a3f9fa1 # v2
         with:
           channel: 'stable'
           flutter-version-file: ./mobile/pubspec.yaml
@@ -55,7 +55,7 @@ jobs:
         working-directory: ./mobile
 
       - name: Find file changes
-        uses: tj-actions/verify-changed-files@v20
+        uses: tj-actions/verify-changed-files@6ed7632824d235029086612d4330d659005af687 # v20
         id: verify-changed-files
         with:
           files: |

.github/workflows/test.yml

@@ -23,9 +23,9 @@ jobs:
       should_run_e2e_server_cli: ${{ steps.found_paths.outputs.e2e == 'true' || steps.found_paths.outputs.server == 'true' || steps.found_paths.outputs.cli == 'true' || steps.should_force.outputs.should_force == 'true' }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - id: found_paths
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@de90cc6fb38fc0963ad72b210f1f284cd68cea36 # v3
         with:
           filters: |
             web:
@@ -61,10 +61,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './server/.nvmrc'
 
@@ -98,10 +98,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './cli/.nvmrc'
 
@@ -139,10 +139,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './cli/.nvmrc'
 
@@ -173,10 +173,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './web/.nvmrc'
 
@@ -218,10 +218,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './e2e/.nvmrc'
 
@@ -257,10 +257,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './server/.nvmrc'
 
@@ -282,12 +282,12 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
         with:
           submodules: 'recursive'
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './e2e/.nvmrc'
 
@@ -324,12 +324,12 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
         with:
           submodules: 'recursive'
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './e2e/.nvmrc'
 
@@ -360,9 +360,9 @@ jobs:
     if: ${{ needs.pre-job.outputs.should_run_mobile == 'true' }}
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - name: Setup Flutter SDK
-        uses: subosito/flutter-action@v2
+        uses: subosito/flutter-action@44ac965b96f18d999802d4b807e3256d5a3f9fa1 # v2
         with:
           channel: 'stable'
           flutter-version-file: ./mobile/pubspec.yaml
@@ -379,10 +379,10 @@ jobs:
       run:
         working-directory: ./machine-learning
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - name: Install uv
-        uses: astral-sh/setup-uv@v5
+        uses: astral-sh/setup-uv@f94ec6bedd8674c4426838e6b50417d36b6ab231 # v5
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@42375524e23c412d93fb67b49958b491fce71c38 # v5
         # TODO: add caching when supported (https://github.com/actions/setup-python/pull/818)
         # with:
         #   python-version: 3.11
@@ -407,7 +407,7 @@ jobs:
     name: ShellCheck
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - name: Run ShellCheck
         uses: ludeeus/action-shellcheck@master
         with:
@@ -421,10 +421,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './server/.nvmrc'
 
@@ -438,7 +438,7 @@ jobs:
         run: make open-api
 
       - name: Find file changes
-        uses: tj-actions/verify-changed-files@v20
+        uses: tj-actions/verify-changed-files@6ed7632824d235029086612d4330d659005af687 # v20
         id: verify-changed-files
         with:
           files: |
@@ -476,10 +476,10 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
 
       - name: Setup Node
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@cdca7365b2dadb8aad0a33bc7601856ffabcc48e # v4
         with:
           node-version-file: './server/.nvmrc'
 
@@ -500,7 +500,7 @@ jobs:
         run: npm run typeorm:migrations:generate ./src/migrations/TestMigration
 
       - name: Find file changes
-        uses: tj-actions/verify-changed-files@v20
+        uses: tj-actions/verify-changed-files@6ed7632824d235029086612d4330d659005af687 # v20
         id: verify-changed-files
         with:
           files: |
@@ -519,7 +519,7 @@ jobs:
           DB_URL: postgres://postgres:postgres@localhost:5432/immich
 
       - name: Find file changes
-        uses: tj-actions/verify-changed-files@v20
+        uses: tj-actions/verify-changed-files@6ed7632824d235029086612d4330d659005af687 # v20
         id: verify-changed-sql-files
         with:
           files: |

.github/workflows/weblate-lock.yml

@@ -11,9 +11,9 @@ jobs:
       should_run: ${{ steps.found_paths.outputs.i18n == 'true' && github.head_ref != 'chore/translations'}}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
       - id: found_paths
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@de90cc6fb38fc0963ad72b210f1f284cd68cea36 # v3
         with:
           filters: |
             i18n:
@@ -36,7 +36,7 @@ jobs:
             exit 1
           fi
       - name: Find Pull Request
-        uses: juliangruber/find-pull-request-action@v1
+        uses: juliangruber/find-pull-request-action@48b6133aa6c826f267ebd33aa2d29470f9d9e7d0 # v1
         id: find-pr
         with:
           branch: chore/translations

cli/package-lock.json

@@ -27,7 +27,7 @@
         "@types/lodash-es": "^4.17.12",
         "@types/micromatch": "^4.0.9",
         "@types/mock-fs": "^4.13.1",
-        "@types/node": "^22.13.9",
+        "@types/node": "^22.13.10",
         "@typescript-eslint/eslint-plugin": "^8.15.0",
         "@typescript-eslint/parser": "^8.15.0",
         "@vitest/coverage-v8": "^3.0.0",
@@ -62,7 +62,7 @@
         "@oazapfts/runtime": "^1.0.2"
       },
       "devDependencies": {
-        "@types/node": "^22.13.9",
+        "@types/node": "^22.13.10",
         "typescript": "^5.3.3"
       }
     },

cli/package.json

@@ -21,7 +21,7 @@
     "@types/lodash-es": "^4.17.12",
     "@types/micromatch": "^4.0.9",
     "@types/mock-fs": "^4.13.1",
-    "@types/node": "^22.13.9",
+    "@types/node": "^22.13.10",
     "@typescript-eslint/eslint-plugin": "^8.15.0",
     "@typescript-eslint/parser": "^8.15.0",
     "@vitest/coverage-v8": "^3.0.0",

docker/docker-compose.dev.yml

@@ -95,12 +95,12 @@ services:
     image: immich-machine-learning-dev:latest
     # extends:
     #   file: hwaccel.ml.yml
-    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
+    #   service: cpu # set to one of [armnn, cuda, rocm, openvino, openvino-wsl, rknn] for accelerated inference
     build:
       context: ../machine-learning
       dockerfile: Dockerfile
       args:
-        - DEVICE=cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
+        - DEVICE=cpu # set to one of [armnn, cuda, rocm, openvino, openvino-wsl, rknn] for accelerated inference
     ports:
       - 3003:3003
     volumes:

docker/docker-compose.prod.yml

@@ -38,12 +38,12 @@ services:
     image: immich-machine-learning:latest
     # extends:
     #   file: hwaccel.ml.yml
-    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
+    #   service: cpu # set to one of [armnn, cuda, rocm, openvino, openvino-wsl, rknn] for accelerated inference
     build:
       context: ../machine-learning
       dockerfile: Dockerfile
       args:
-        - DEVICE=cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference
+        - DEVICE=cpu # set to one of [armnn, cuda, rocm, openvino, openvino-wsl, rknn] for accelerated inference
     ports:
       - 3003:3003
     volumes:
@@ -77,22 +77,12 @@ services:
       - 5432:5432
     healthcheck:
       test: >-
-        pg_isready --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" || exit 1;
+        pg_isready --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" || exit 1; Chksum="$$(psql --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" --tuples-only --no-align --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
-        Chksum="$$(psql --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" --tuples-only --no-align
-        --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')";
-        echo "checksum failure count is $$Chksum";
-        [ "$$Chksum" = '0' ] || exit 1
       interval: 5m
       start_interval: 30s
       start_period: 5m
     command: >-
-      postgres
+      postgres -c shared_preload_libraries=vectors.so -c 'search_path="$$user", public, vectors' -c logging_collector=on -c max_wal_size=2GB -c shared_buffers=512MB -c wal_compression=on
-      -c shared_preload_libraries=vectors.so
-      -c 'search_path="$$user", public, vectors'
-      -c logging_collector=on
-      -c max_wal_size=2GB
-      -c shared_buffers=512MB
-      -c wal_compression=on
     restart: always
 
   # set IMMICH_TELEMETRY_INCLUDE=all in .env to enable metrics
@@ -109,7 +99,7 @@ services:
   # add data source for http://immich-prometheus:9090 to get started
   immich-grafana:
     container_name: immich_grafana
-    command: ['./run.sh', '-disable-reporting']
+    command: [ './run.sh', '-disable-reporting' ]
     ports:
       - 3000:3000
     image: grafana/grafana:11.5.2-ubuntu@sha256:8b5858c447e06fd7a89006b562ba7bba7c4d5813600c7982374c41852adefaeb

docker/docker-compose.yml

@@ -33,12 +33,12 @@ services:
 
   immich-machine-learning:
     container_name: immich_machine_learning
-    # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
+    # For hardware acceleration, add one of -[armnn, cuda, rocm, openvino, rknn] to the image tag.
     # Example tag: ${IMMICH_VERSION:-release}-cuda
     image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
     # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
     #   file: hwaccel.ml.yml
-    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
+    #   service: cpu # set to one of [armnn, cuda, rocm, openvino, openvino-wsl, rknn] for accelerated inference - use the `-wsl` version for WSL2 where applicable
     volumes:
       - model-cache:/cache
     env_file:
@@ -67,22 +67,12 @@ services:
       - ${DB_DATA_LOCATION}:/var/lib/postgresql/data
     healthcheck:
       test: >-
-        pg_isready --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" || exit 1;
+        pg_isready --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" || exit 1; Chksum="$$(psql --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" --tuples-only --no-align --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
-        Chksum="$$(psql --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" --tuples-only --no-align
-        --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')";
-        echo "checksum failure count is $$Chksum";
-        [ "$$Chksum" = '0' ] || exit 1
       interval: 5m
       start_interval: 30s
       start_period: 5m
     command: >-
-      postgres
+      postgres -c shared_preload_libraries=vectors.so -c 'search_path="$$user", public, vectors' -c logging_collector=on -c max_wal_size=2GB -c shared_buffers=512MB -c wal_compression=on
-      -c shared_preload_libraries=vectors.so
-      -c 'search_path="$$user", public, vectors'
-      -c logging_collector=on
-      -c max_wal_size=2GB
-      -c shared_buffers=512MB
-      -c wal_compression=on
     restart: always
 
 volumes:

docker/hwaccel.ml.yml

@@ -14,6 +14,13 @@ services:
       - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
       - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)
   
+  rknn:
+    security_opt:
+      - systempaths=unconfined
+      - apparmor=unconfined
+    devices:
+      - /dev/dri:/dev/dri
+
   cpu: {}
 
   cuda:
@@ -26,6 +33,13 @@ services:
               capabilities:
                 - gpu
 
+  rocm:
+    group_add:
+      - video
+    devices:
+      - /dev/dri:/dev/dri
+      - /dev/kfd:/dev/kfd
+
   openvino:
     device_cgroup_rules:
       - 'c 189:* rmw'

docs/docs/administration/server-commands.md

@@ -11,6 +11,7 @@ The `immich-server` docker image comes preinstalled with an administrative CLI (
 | `enable-oauth-login`     | Enable OAuth login                    |
 | `disable-oauth-login`    | Disable OAuth login                   |
 | `list-users`             | List Immich users                     |
+| `version`                | Print Immich version                  |
 
 ## How to run a command
 
@@ -80,3 +81,10 @@ immich-admin list-users
   }
 ]
 ```
+
+Print Immich Version
+
+```
+immich-admin version
+v1.129.0
+```

docs/docs/features/ml-hardware-acceleration.md

@@ -11,7 +11,9 @@ You do not need to redo any machine learning jobs after enabling hardware accele
 
 - ARM NN (Mali)
 - CUDA (NVIDIA GPUs with [compute capability](https://developer.nvidia.com/cuda-gpus) 5.2 or higher)
+- ROCm (AMD GPUs)
 - OpenVINO (Intel GPUs such as Iris Xe and Arc)
+- RKNN (Rockchip)
 
 ## Limitations
 
@@ -19,6 +21,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele
 - Only Linux and Windows (through WSL2) servers are supported.
 - ARM NN is only supported on devices with Mali GPUs. Other Arm devices are not supported.
 - Some models may not be compatible with certain backends. CUDA is the most reliable.
+- Search latency isn't improved by ARM NN due to model compatibility issues preventing its use. However, smart search jobs do make use of ARM NN.
 
 ## Prerequisites
 
@@ -33,6 +36,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele
   - The `hwaccel.ml.yml` file assumes the path to it is `/usr/lib/libmali.so`, so update accordingly if it is elsewhere
   - The `hwaccel.ml.yml` file assumes an additional file `/lib/firmware/mali_csffw.bin`, so update accordingly if your device's driver does not require this file
 - Optional: Configure your `.env` file, see [environment variables](/docs/install/environment-variables) for ARM NN specific settings
+  - In particular, the `MACHINE_LEARNING_ANN_FP16_TURBO` can significantly improve performance at the cost of very slightly lower accuracy
 
 #### CUDA
 
@@ -41,22 +45,38 @@ You do not need to redo any machine learning jobs after enabling hardware accele
 - The installed driver must be >= 535 (it must support CUDA 12.2).
 - On Linux (except for WSL2), you also need to have [NVIDIA Container Toolkit][nvct] installed.
 
+#### ROCm
+
+- The GPU must be supported by ROCm. If it isn't officially supported, you can attempt to use the `HSA_OVERRIDE_GFX_VERSION` environmental variable: `HSA_OVERRIDE_GFX_VERSION=<a supported version, e.g. 10.3.0>`. If this doesn't work, you might need to also set `HSA_USE_SVM=0`.
+- The ROCm image is quite large and requires at least 35GiB of free disk space. However, pulling later updates to the service through Docker will generally only amount to a few hundred megabytes as the rest will be cached.
+- This backend is new and may experience some issues. For example, GPU power consumption can be higher than usual after running inference, even if the machine learning service is idle. In this case, it will only go back to normal after being idle for 5 minutes (configurable with the [MACHINE_LEARNING_MODEL_TTL](/docs/install/environment-variables) setting).
+
 #### OpenVINO
 
 - Integrated GPUs are more likely to experience issues than discrete GPUs, especially for older processors or servers with low RAM.
 - Ensure the server's kernel version is new enough to use the device for hardware accceleration.
 - Expect higher RAM usage when using OpenVINO compared to CPU processing.
 
+#### RKNN
+
+- You must have a supported Rockchip SoC: only RK3566, RK3568, RK3576 and RK3588 are supported at this moment.
+- Make sure you have the appropriate linux kernel driver installed
+  - This is usually pre-installed on the device vendor's Linux images
+- RKNPU driver V0.9.8 or later must be available in the host server
+  - You may confirm this by running `cat /sys/kernel/debug/rknpu/version` to check the version
+- Optional: Configure your `.env` file, see [environment variables](/docs/install/environment-variables) for RKNN specific settings
+  - In particular, setting `MACHINE_LEARNING_RKNN_THREADS` to 2 or 3 can _dramatically_ improve performance for RK3576 and RK3588 compared to the default of 1, at the expense of multiplying the amount of RAM each model uses by that amount.
+
 ## Setup
 
 1. If you do not already have it, download the latest [`hwaccel.ml.yml`][hw-file] file and ensure it's in the same folder as the `docker-compose.yml`.
 2. In the `docker-compose.yml` under `immich-machine-learning`, uncomment the `extends` section and change `cpu` to the appropriate backend.
-3. Still in `immich-machine-learning`, add one of -[armnn, cuda, openvino] to the `image` section's tag at the end of the line.
+3. Still in `immich-machine-learning`, add one of -[armnn, cuda, rocm, openvino] to the `image` section's tag at the end of the line.
 4. Redeploy the `immich-machine-learning` container with these updated settings.
 
 ### Confirming Device Usage
 
-You can confirm the device is being recognized and used by checking its utilization. There are many tools to display this, such as `nvtop` for NVIDIA or Intel and `intel_gpu_top` for Intel.
+You can confirm the device is being recognized and used by checking its utilization. There are many tools to display this, such as `nvtop` for NVIDIA or Intel, `intel_gpu_top` for Intel, and `radeontop` for AMD.
 
 You can also check the logs of the `immich-machine-learning` container. When a Smart Search or Face Detection job begins, or when you search with text in Immich, you should either see a log for `Available ORT providers` containing the relevant provider (e.g. `CUDAExecutionProvider` in the case of CUDA), or a `Loaded ANN model` log entry without errors in the case of ARM NN.
 
@@ -127,3 +147,12 @@ Note that you should increase job concurrencies to increase overall utilization
 - If you encounter an error when a model is running, try a different model to see if the issue is model-specific.
 - You may want to increase concurrency past the default for higher utilization. However, keep in mind that this will also increase VRAM consumption.
 - Larger models benefit more from hardware acceleration, if you have the VRAM for them.
+- Compared to ARM NN, RKNPU has:
+  - Wider model support (including for search, which ARM NN does not accelerate)
+  - Less heat generation
+  - Very slightly lower accuracy (RKNPU always uses FP16, while ARM NN by default uses higher precision FP32 unless `MACHINE_LEARNING_ANN_FP16_TURBO` is enabled)
+  - Varying speed (tested on RK3588):
+    - If `MACHINE_LEARNING_RKNN_THREADS` is at the default of 1, RKNPU will have substantially lower throughput for ML jobs than ARM NN in most cases, but similar latency (such as when searching)
+    - If `MACHINE_LEARNING_RKNN_THREADS` is set to 3, it will be somewhat faster than ARM NN at FP32, but somewhat slower than ARM NN if `MACHINE_LEARNING_ANN_FP16_TURBO` is enabled
+    - When other tasks also use the GPU (like transcoding), RKNPU has a significant advantage over ARM NN as it uses the otherwise idle NPU instead of competing for GPU usage
+  - Lower RAM usage if `MACHINE_LEARNING_RKNN_THREADS` is at the default of 1, but significantly higher if greater than 1 (which is necessary for it to fully utilize the NPU and hence be comparable in speed to ARM NN)

docs/docs/guides/remote-machine-learning.md

@@ -23,12 +23,12 @@ name: immich_remote_ml
 services:
   immich-machine-learning:
     container_name: immich_machine_learning
-    # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
+    # For hardware acceleration, add one of -[armnn, cuda, rocm, openvino] to the image tag.
     # Example tag: ${IMMICH_VERSION:-release}-cuda
     image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
     # extends:
     #   file: hwaccel.ml.yml
-    #   service: # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
+    #   service: # set to one of [armnn, cuda, rocm, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
     volumes:
       - model-cache:/cache
     restart: always

docs/docs/install/environment-variables.md

@@ -170,6 +170,8 @@ Redis (Sentinel) URL example JSON before encoding:
 | `MACHINE_LEARNING_MAX_BATCH_SIZE__FACIAL_RECOGNITION`       | Set the maximum number of faces that will be processed at once by the facial recognition model      |  None (`1` if using OpenVINO)   | machine learning |
 | `MACHINE_LEARNING_PING_TIMEOUT`                             | How long (ms) to wait for a PING response when checking if an ML server is available                |             `2000`              | server           |
 | `MACHINE_LEARNING_AVAILABILITY_BACKOFF_TIME`                | How long to ignore ML servers that are offline before trying again                                  |             `30000`             | server           |
+| `MACHINE_LEARNING_RKNN`                                     | Enable RKNN hardware acceleration if supported                                                      |             `True`              | machine learning |
+| `MACHINE_LEARNING_RKNN_THREADS`                             | How many threads of RKNN runtime should be spinned up while inferencing.                            |               `1`               | machine learning |
 
 \*1: It is recommended to begin with this parameter when changing the concurrency levels of the machine learning service and then tune the other ones.
 

e2e/package-lock.json

@@ -15,7 +15,7 @@
         "@immich/sdk": "file:../open-api/typescript-sdk",
         "@playwright/test": "^1.44.1",
         "@types/luxon": "^3.4.2",
-        "@types/node": "^22.13.9",
+        "@types/node": "^22.13.10",
         "@types/oidc-provider": "^8.5.1",
         "@types/pg": "^8.11.0",
         "@types/pngjs": "^6.0.4",
@@ -67,7 +67,7 @@
         "@types/lodash-es": "^4.17.12",
         "@types/micromatch": "^4.0.9",
         "@types/mock-fs": "^4.13.1",
-        "@types/node": "^22.13.9",
+        "@types/node": "^22.13.10",
         "@typescript-eslint/eslint-plugin": "^8.15.0",
         "@typescript-eslint/parser": "^8.15.0",
         "@vitest/coverage-v8": "^3.0.0",
@@ -102,7 +102,7 @@
         "@oazapfts/runtime": "^1.0.2"
       },
       "devDependencies": {
-        "@types/node": "^22.13.9",
+        "@types/node": "^22.13.10",
         "typescript": "^5.3.3"
       }
     },

e2e/package.json

@@ -25,7 +25,7 @@
     "@immich/sdk": "file:../open-api/typescript-sdk",
     "@playwright/test": "^1.44.1",
     "@types/luxon": "^3.4.2",
-    "@types/node": "^22.13.9",
+    "@types/node": "^22.13.10",
     "@types/oidc-provider": "^8.5.1",
     "@types/pg": "^8.11.0",
     "@types/pngjs": "^6.0.4",

e2e/src/web/specs/shared-link.e2e-spec.ts

@@ -45,7 +45,7 @@ test.describe('Shared Links', () => {
     await page.goto(`/share/${sharedLink.key}`);
     await page.getByRole('heading', { name: 'Test Album' }).waitFor();
     await page.locator(`[data-asset-id="${asset.id}"]`).hover();
-    await page.waitForSelector('#asset-group-by-date svg');
+    await page.waitForSelector('[data-group] svg');
     await page.getByRole('checkbox').click();
     await page.getByRole('button', { name: 'Download' }).click();
     await page.getByText('DOWNLOADING', { exact: true }).waitFor();

i18n/en.json

@@ -1082,7 +1082,9 @@
   "remove_url": "Remove URL",
   "remove_user": "Remove user",
   "removed_api_key": "Removed API Key: {name}",
+  "remove_memory": "Remove memory",
   "removed_memory": "Removed memory",
+  "remove_photo_from_memory": "Remove photo from this memory",
   "removed_photo_from_memory": "Removed photo from memory",
   "removed_from_archive": "Removed from archive",
   "removed_from_favorites": "Removed from favorites",

machine-learning/.gitignore

@@ -1,5 +1,24 @@
 *.zip
 *.onnx
+*.rknn
+*.npy
+*_attr__value
+*.weight
+*.bias
+onnx__*
+*in_proj_bias
+*.proj
+*.latent
+*.pos_embed
+vocab.txt
+export/immich_model_exporter/models/**/README.md
+tokenizer.json
+tokenizer_config.json
+special_tokens_map.json
+preprocess_cfg.json
+config.json
+merges.txt
+vocab.json
 upload/
 venv/
 __pycache__/

machine-learning/Dockerfile

@@ -15,6 +15,36 @@ RUN mkdir /opt/armnn && \
     cd /opt/ann && \
     sh build.sh
 
+FROM builder-cpu AS builder-rknn
+
+# Warning: 25GiB+ disk space required to pull this image
+# TODO: find a way to reduce the image size
+FROM rocm/dev-ubuntu-22.04:6.3.4-complete AS builder-rocm
+
+WORKDIR /code
+
+RUN apt-get update && apt-get install -y --no-install-recommends wget git python3.10-venv
+RUN wget -nv https://github.com/Kitware/CMake/releases/download/v3.30.1/cmake-3.30.1-linux-x86_64.sh && \
+    chmod +x cmake-3.30.1-linux-x86_64.sh && \
+    mkdir -p /code/cmake-3.30.1-linux-x86_64 && \
+    ./cmake-3.30.1-linux-x86_64.sh --skip-license --prefix=/code/cmake-3.30.1-linux-x86_64 && \
+    rm cmake-3.30.1-linux-x86_64.sh
+
+ENV PATH=/code/cmake-3.30.1-linux-x86_64/bin:${PATH}
+
+RUN git clone --single-branch --branch v1.20.1 --recursive "https://github.com/Microsoft/onnxruntime" onnxruntime
+WORKDIR /code/onnxruntime
+# Fix for multi-threading based on comments in https://github.com/microsoft/onnxruntime/pull/19567
+# TODO: find a way to fix this without disabling algo caching
+COPY ./patches/* /tmp/
+RUN git apply /tmp/*.patch
+
+RUN /bin/sh ./dockerfiles/scripts/install_common_deps.sh
+# Note: the `parallel` setting uses a substantial amount of RAM
+RUN ./build.sh --allow_running_as_root --config Release --build_wheel --update --build --parallel 17 --cmake_extra_defines\
+    ONNXRUNTIME_VERSION=1.20.1 --skip_tests --use_rocm --rocm_home=/opt/rocm
+RUN mv /code/onnxruntime/build/Linux/Release/dist/*.whl /opt/
+
 FROM builder-${DEVICE} AS builder
 
 ARG DEVICE
@@ -30,6 +60,9 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     --mount=type=bind,source=uv.lock,target=uv.lock \
     --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
     uv sync --frozen --extra ${DEVICE} --no-dev --no-editable --no-install-project --compile-bytecode --no-progress --active --link-mode copy
+RUN if [ "$DEVICE" = "rocm" ]; then \
+    uv pip install /opt/onnxruntime_rocm-*.whl; \
+    fi
 
 FROM python:3.11-slim-bookworm@sha256:614c8691ab74150465ec9123378cd4dde7a6e57be9e558c3108df40664667a4c AS prod-cpu
 
@@ -37,10 +70,10 @@ FROM prod-cpu AS prod-openvino
 
 RUN apt-get update && \
     apt-get install --no-install-recommends -yqq ocl-icd-libopencl1 wget && \
-    wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17384.11/intel-igc-core_1.0.17384.11_amd64.deb && \
+    wget -nv https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17384.11/intel-igc-core_1.0.17384.11_amd64.deb && \
-    wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17384.11/intel-igc-opencl_1.0.17384.11_amd64.deb && \
+    wget -nv https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17384.11/intel-igc-opencl_1.0.17384.11_amd64.deb && \
-    wget https://github.com/intel/compute-runtime/releases/download/24.31.30508.7/intel-opencl-icd_24.31.30508.7_amd64.deb && \
+    wget -nv https://github.com/intel/compute-runtime/releases/download/24.31.30508.7/intel-opencl-icd_24.31.30508.7_amd64.deb && \
-    wget https://github.com/intel/compute-runtime/releases/download/24.31.30508.7/libigdgmm12_22.4.1_amd64.deb && \
+    wget -nv https://github.com/intel/compute-runtime/releases/download/24.31.30508.7/libigdgmm12_22.4.1_amd64.deb && \
     dpkg -i *.deb && \
     rm *.deb && \
     apt-get remove wget -yqq && \
@@ -57,6 +90,8 @@ COPY --from=builder-cuda /usr/local/bin/python3 /usr/local/bin/python3
 COPY --from=builder-cuda /usr/local/lib/python3.11 /usr/local/lib/python3.11
 COPY --from=builder-cuda /usr/local/lib/libpython3.11.so /usr/local/lib/libpython3.11.so
 
+FROM rocm/dev-ubuntu-22.04:6.3.4-complete AS prod-rocm
+
 FROM prod-cpu AS prod-armnn
 
 ENV LD_LIBRARY_PATH=/opt/armnn
@@ -77,11 +112,14 @@ COPY --from=builder-armnn \
     /opt/ann/build.sh \
     /opt/armnn/
 
+FROM prod-cpu AS prod-rknn
+
 FROM prod-${DEVICE} AS prod
+
 ARG DEVICE
 
 RUN apt-get update && \
-    apt-get install -y --no-install-recommends tini $(if ! [ "$DEVICE" = "openvino" ]; then echo "libmimalloc2.0"; fi) && \
+    apt-get install -y --no-install-recommends tini $(if ! [ "$DEVICE" = "openvino" ] && ! [ "$DEVICE" = "rocm" ]; then echo "libmimalloc2.0"; fi) && \
     apt-get autoremove -yqq && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*

machine-learning/README.md

@@ -7,7 +7,7 @@
 
 This project uses [uv](https://docs.astral.sh/uv/getting-started/installation/), so be sure to install it first.
 Running `uv sync --extra cpu` will install everything you need in an isolated virtual environment.
-CUDA and OpenVINO are supported as acceleration APIs. To use them, you can replace `--group cpu` with either of `--group cuda` or `--group openvino`. In the case of CUDA, a [compute capability](https://developer.nvidia.com/cuda-gpus) of 5.2 or higher is required.
+CUDA, ROCM and OpenVINO are supported as acceleration APIs. To use them, you can replace `--extra cpu` with either of `--extra cuda`, `--extra rocm` or `--extra openvino`. In the case of CUDA, a [compute capability](https://developer.nvidia.com/cuda-gpus) of 5.2 or higher is required.
 
 To add or remove dependencies, you can use the commands `uv add $PACKAGE_NAME` and `uv remove $PACKAGE_NAME`, respectively.
 Be sure to commit the `uv.lock` and `pyproject.toml` files with `uv lock` to reflect any changes in dependencies.

machine-learning/app/config.py

@@ -64,6 +64,8 @@ class Settings(BaseSettings):
     ann: bool = True
     ann_fp16_turbo: bool = False
     ann_tuning_level: int = 2
+    rknn: bool = True
+    rknn_threads: int = 1
     preload: PreloadModelData | None = None
     max_batch_size: MaxBatchSize | None = None
 

machine-learning/app/conftest.py

@@ -136,6 +136,12 @@ def ann_session() -> Iterator[mock.Mock]:
         yield mocked
 
 
+@pytest.fixture(scope="function")
+def rknn_session() -> Iterator[mock.Mock]:
+    with mock.patch("app.sessions.rknn.RknnPoolExecutor") as mocked:
+        yield mocked
+
+
 @pytest.fixture(scope="function")
 def rmtree() -> Iterator[mock.Mock]:
     with mock.patch("app.models.base.rmtree", autospec=True) as mocked:

machine-learning/app/main.py

@@ -226,9 +226,9 @@ async def load(model: InferenceModel) -> InferenceModel:
             except FileNotFoundError as e:
                 if model.model_format == ModelFormat.ONNX:
                     raise e
-                log.exception(e)
                 log.warning(
-                    f"{model.model_format.upper()} is available, but model '{model.model_name}' does not support it."
+                    f"{model.model_format.upper()} is available, but model '{model.model_name}' does not support it.",
+                    exc_info=e,
                 )
                 model.model_format = ModelFormat.ONNX
                 model.load()

machine-learning/app/models/base.py

@@ -8,6 +8,7 @@ from typing import Any, ClassVar
 from huggingface_hub import snapshot_download
 
 import ann.ann
+import app.sessions.rknn as rknn
 from app.sessions.ort import OrtSession
 
 from ..config import clean_name, log, settings
@@ -66,12 +67,17 @@ class InferenceModel(ABC):
         pass
 
     def _download(self) -> None:
-        ignore_patterns = [] if self.model_format == ModelFormat.ARMNN else ["*.armnn"]
+        ignored_patterns: dict[ModelFormat, list[str]] = {
+            ModelFormat.ONNX: ["*.armnn", "*.rknn"],
+            ModelFormat.ARMNN: ["*.rknn"],
+            ModelFormat.RKNN: ["*.armnn"],
+        }
+
         snapshot_download(
             f"immich-app/{clean_name(self.model_name)}",
             cache_dir=self.cache_dir,
             local_dir=self.cache_dir,
-            ignore_patterns=ignore_patterns,
+            ignore_patterns=ignored_patterns.get(self.model_format, []),
         )
 
     def _load(self) -> ModelSession:
@@ -108,17 +114,25 @@ class InferenceModel(ABC):
                 session: ModelSession = AnnSession(model_path)
             case ".onnx":
                 session = OrtSession(model_path)
+            case ".rknn":
+                session = rknn.RknnSession(model_path)
             case _:
                 raise ValueError(f"Unsupported model file type: {model_path.suffix}")
         return session
 
+    def model_path_for_format(self, model_format: ModelFormat) -> Path:
+        model_path_prefix = rknn.model_prefix if model_format == ModelFormat.RKNN else None
+        if model_path_prefix:
+            return self.model_dir / model_path_prefix / f"model.{model_format}"
+        return self.model_dir / f"model.{model_format}"
+
     @property
     def model_dir(self) -> Path:
         return self.cache_dir / self.model_type.value
 
     @property
     def model_path(self) -> Path:
-        return self.model_dir / f"model.{self.model_format}"
+        return self.model_path_for_format(self.model_format)
 
     @property
     def model_task(self) -> ModelTask:
@@ -155,4 +169,9 @@ class InferenceModel(ABC):
 
     @property
     def _model_format_default(self) -> ModelFormat:
-        return ModelFormat.ARMNN if ann.ann.is_available and settings.ann else ModelFormat.ONNX
+        if rknn.is_available:
+            return ModelFormat.RKNN
+        elif ann.ann.is_available and settings.ann:
+            return ModelFormat.ARMNN
+        else:
+            return ModelFormat.ONNX

machine-learning/app/models/constants.py

@@ -44,6 +44,18 @@ _OPENCLIP_MODELS = {
     "nllb-clip-base-siglip__v1",
     "nllb-clip-large-siglip__mrl",
     "nllb-clip-large-siglip__v1",
+    "ViT-B-16-SigLIP2__webli",
+    "ViT-B-32-SigLIP2-256__webli",
+    "ViT-L-16-SigLIP2-256__webli",
+    "ViT-L-16-SigLIP2-384__webli",
+    "ViT-L-16-SigLIP2-512__webli",
+    "ViT-SO400M-14-SigLIP2-378__webli",
+    "ViT-SO400M-14-SigLIP2__webli",
+    "ViT-SO400M-16-SigLIP2-256__webli",
+    "ViT-SO400M-16-SigLIP2-384__webli",
+    "ViT-SO400M-16-SigLIP2-512__webli",
+    "ViT-gopt-16-SigLIP2-256__webli",
+    "ViT-gopt-16-SigLIP2-384__webli",
 }
 
 
@@ -63,7 +75,15 @@ _INSIGHTFACE_MODELS = {
 }
 
 
-SUPPORTED_PROVIDERS = ["CUDAExecutionProvider", "OpenVINOExecutionProvider", "CPUExecutionProvider"]
+SUPPORTED_PROVIDERS = [
+    "CUDAExecutionProvider",
+    "ROCMExecutionProvider",
+    "OpenVINOExecutionProvider",
+    "CPUExecutionProvider",
+]
+
+RKNN_SUPPORTED_SOCS = ["rk3566", "rk3568", "rk3576", "rk3588"]
+RKNN_COREMASK_SUPPORTED_SOCS = ["rk3576", "rk3588"]
 
 
 def get_model_source(model_name: str) -> ModelSource | None:

machine-learning/app/models/facial_recognition/recognition.py

@@ -31,7 +31,7 @@ class FaceRecognizer(InferenceModel):
             self._add_batch_axis(self.model_path)
             session = self._make_session(self.model_path)
         self.model = ArcFaceONNX(
-            self.model_path.with_suffix(".onnx").as_posix(),
+            self.model_path_for_format(ModelFormat.ONNX).as_posix(),
             session=session,
         )
         return session

machine-learning/app/schemas.py

@@ -35,6 +35,7 @@ class ModelType(StrEnum):
 class ModelFormat(StrEnum):
     ARMNN = "armnn"
     ONNX = "onnx"
+    RKNN = "rknn"
 
 
 class ModelSource(StrEnum):

machine-learning/app/sessions/ort.py

@@ -88,7 +88,7 @@ class OrtSession:
             match provider:
                 case "CPUExecutionProvider":
                     options = {"arena_extend_strategy": "kSameAsRequested"}
-                case "CUDAExecutionProvider":
+                case "CUDAExecutionProvider" | "ROCMExecutionProvider":
                     options = {"arena_extend_strategy": "kSameAsRequested", "device_id": settings.device_id}
                 case "OpenVINOExecutionProvider":
                     options = {

machine-learning/app/sessions/rknn/__init__.py

@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any, NamedTuple
+
+import numpy as np
+from numpy.typing import NDArray
+
+from app.config import log, settings
+from app.schemas import SessionNode
+
+from .rknnpool import RknnPoolExecutor, is_available, soc_name
+
+is_available = is_available and settings.rknn
+model_prefix = Path("rknpu") / soc_name if is_available and soc_name is not None else None
+
+
+def run_inference(rknn_lite: Any, input: list[NDArray[np.float32]]) -> list[NDArray[np.float32]]:
+    outputs: list[NDArray[np.float32]] = rknn_lite.inference(inputs=input, data_format="nchw")
+    return outputs
+
+
+input_output_mapping: dict[str, dict[str, Any]] = {
+    "detection": {
+        "input": {"norm_tensor:0": (1, 3, 640, 640)},
+        "output": {
+            "norm_tensor:1": (12800, 1),
+            "norm_tensor:2": (3200, 1),
+            "norm_tensor:3": (800, 1),
+            "norm_tensor:4": (12800, 4),
+            "norm_tensor:5": (3200, 4),
+            "norm_tensor:6": (800, 4),
+            "norm_tensor:7": (12800, 10),
+            "norm_tensor:8": (3200, 10),
+            "norm_tensor:9": (800, 10),
+        },
+    },
+    "recognition": {"input": {"norm_tensor:0": (1, 3, 112, 112)}, "output": {"norm_tensor:1": (1, 512)}},
+}
+
+
+class RknnSession:
+    def __init__(self, model_path: Path) -> None:
+        self.model_type = "detection" if "detection" in model_path.parts else "recognition"
+        self.tpe = settings.rknn_threads
+
+        log.info(f"Loading RKNN model from {model_path} with {self.tpe} threads.")
+        self.rknnpool = RknnPoolExecutor(model_path=model_path.as_posix(), tpes=self.tpe, func=run_inference)
+        log.info(f"Loaded RKNN model from {model_path} with {self.tpe} threads.")
+
+    def get_inputs(self) -> list[SessionNode]:
+        return [RknnNode(name=k, shape=v) for k, v in input_output_mapping[self.model_type]["input"].items()]
+
+    def get_outputs(self) -> list[SessionNode]:
+        return [RknnNode(name=k, shape=v) for k, v in input_output_mapping[self.model_type]["output"].items()]
+
+    def run(
+        self,
+        output_names: list[str] | None,
+        input_feed: dict[str, NDArray[np.float32]] | dict[str, NDArray[np.int32]],
+        run_options: Any = None,
+    ) -> list[NDArray[np.float32]]:
+        input_data: list[NDArray[np.float32]] = [np.ascontiguousarray(v) for v in input_feed.values()]
+        self.rknnpool.put(input_data)
+        res = self.rknnpool.get()
+        if res is None:
+            raise RuntimeError("RKNN inference failed!")
+        return res
+
+
+class RknnNode(NamedTuple):
+    name: str | None
+    shape: tuple[int, ...]
+
+
+__all__ = ["RknnSession", "RknnNode", "is_available", "soc_name", "model_prefix"]

machine-learning/app/sessions/rknn/rknnpool.py

@@ -0,0 +1,91 @@
+# This code is from leafqycc/rknn-multi-threaded
+# Following Apache License 2.0
+
+import logging
+from concurrent.futures import Future, ThreadPoolExecutor
+from pathlib import Path
+from queue import Queue
+from typing import Callable
+
+import numpy as np
+from numpy.typing import NDArray
+
+from app.config import log
+from app.models.constants import RKNN_COREMASK_SUPPORTED_SOCS, RKNN_SUPPORTED_SOCS
+
+
+def get_soc(device_tree_path: Path | str) -> str | None:
+    try:
+        with Path(device_tree_path).open() as f:
+            device_compatible_str = f.read()
+            for soc in RKNN_SUPPORTED_SOCS:
+                if soc in device_compatible_str:
+                    return soc
+            log.warning("Device is not supported for RKNN")
+    except OSError as e:
+        log.warning(f"Could not read {device_tree_path}. Reason: %s", e)
+    return None
+
+
+soc_name = None
+is_available = False
+try:
+    from rknnlite.api import RKNNLite
+
+    soc_name = get_soc("/proc/device-tree/compatible")
+    is_available = soc_name is not None
+except ImportError:
+    log.debug("RKNN is not available")
+
+
+def init_rknn(model_path: str) -> "RKNNLite":
+    if not is_available:
+        raise RuntimeError("rknn is not available!")
+    rknn_lite = RKNNLite()
+    rknn_lite.rknn_log.logger.setLevel(logging.ERROR)
+    ret = rknn_lite.load_rknn(model_path)
+    if ret != 0:
+        raise RuntimeError("Failed to load RKNN model")
+
+    if soc_name in RKNN_COREMASK_SUPPORTED_SOCS:
+        ret = rknn_lite.init_runtime(core_mask=RKNNLite.NPU_CORE_AUTO)
+    else:
+        ret = rknn_lite.init_runtime()  # Please do not set this parameter on other platforms.
+
+    if ret != 0:
+        raise RuntimeError("Failed to inititalize RKNN runtime environment")
+
+    return rknn_lite
+
+
+class RknnPoolExecutor:
+    def __init__(
+        self,
+        model_path: str,
+        tpes: int,
+        func: Callable[["RKNNLite", list[NDArray[np.float32]]], list[NDArray[np.float32]]],
+    ) -> None:
+        self.tpes = tpes
+        self.queue: Queue[Future[list[NDArray[np.float32]]]] = Queue()
+        self.rknn_pool = [init_rknn(model_path) for _ in range(tpes)]
+        self.pool = ThreadPoolExecutor(max_workers=tpes)
+        self.func = func
+        self.num = 0
+
+    def put(self, inputs: list[NDArray[np.float32]]) -> None:
+        self.queue.put(self.pool.submit(self.func, self.rknn_pool[self.num % self.tpes], inputs))
+        self.num += 1
+
+    def get(self) -> list[NDArray[np.float32]] | None:
+        if self.queue.empty():
+            return None
+        fut = self.queue.get()
+        return fut.result()
+
+    def release(self) -> None:
+        self.pool.shutdown()
+        for rknn_lite in self.rknn_pool:
+            rknn_lite.release()
+
+    def __del__(self) -> None:
+        self.release()

machine-learning/app/test_main.py

@@ -25,6 +25,7 @@ from app.models.facial_recognition.detection import FaceDetector
 from app.models.facial_recognition.recognition import FaceRecognizer
 from app.sessions.ann import AnnSession
 from app.sessions.ort import OrtSession
+from app.sessions.rknn import RknnSession, run_inference
 
 from .config import Settings, settings
 from .models.base import InferenceModel
@@ -69,6 +70,14 @@ class TestBase:
 
         assert encoder.model_format == ModelFormat.ARMNN
 
+    def test_sets_default_model_format_to_rknn_if_available(self, mocker: MockerFixture) -> None:
+        mocker.patch.object(settings, "rknn", True)
+        mocker.patch("app.sessions.rknn.is_available", True)
+
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+
+        assert encoder.model_format == ModelFormat.RKNN
+
     def test_casts_cache_dir_string_to_path(self) -> None:
         cache_dir = "/test_cache"
         encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=cache_dir)
@@ -125,7 +134,7 @@ class TestBase:
             "immich-app/ViT-B-32__openai",
             cache_dir=encoder.cache_dir,
             local_dir=encoder.cache_dir,
-            ignore_patterns=["*.armnn"],
+            ignore_patterns=["*.armnn", "*.rknn"],
         )
 
     def test_download_downloads_armnn_if_preferred_format(self, snapshot_download: mock.Mock) -> None:
@@ -136,7 +145,18 @@ class TestBase:
             "immich-app/ViT-B-32__openai",
             cache_dir=encoder.cache_dir,
             local_dir=encoder.cache_dir,
-            ignore_patterns=[],
+            ignore_patterns=["*.rknn"],
+        )
+
+    def test_download_downloads_rknn_if_preferred_format(self, snapshot_download: mock.Mock) -> None:
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", model_format=ModelFormat.RKNN)
+        encoder.download()
+
+        snapshot_download.assert_called_once_with(
+            "immich-app/ViT-B-32__openai",
+            cache_dir=encoder.cache_dir,
+            local_dir=encoder.cache_dir,
+            ignore_patterns=["*.armnn"],
         )
 
     def test_throws_exception_if_model_path_does_not_exist(
@@ -160,6 +180,7 @@ class TestOrtSession:
     OV_EP = ["OpenVINOExecutionProvider", "CPUExecutionProvider"]
     CUDA_EP_OUT_OF_ORDER = ["CPUExecutionProvider", "CUDAExecutionProvider"]
     TRT_EP = ["TensorrtExecutionProvider", "CUDAExecutionProvider", "CPUExecutionProvider"]
+    ROCM_EP = ["ROCMExecutionProvider", "CPUExecutionProvider"]
 
     @pytest.mark.providers(CPU_EP)
     def test_sets_cpu_provider(self, providers: list[str]) -> None:
@@ -199,6 +220,12 @@ class TestOrtSession:
 
         assert session.providers == self.CUDA_EP
 
+    @pytest.mark.providers(ROCM_EP)
+    def test_uses_rocm(self, providers: list[str]) -> None:
+        session = OrtSession("ViT-B-32__openai")
+
+        assert session.providers == self.ROCM_EP
+
     def test_sets_provider_kwarg(self) -> None:
         providers = ["CUDAExecutionProvider"]
         session = OrtSession("ViT-B-32__openai", providers=providers)
@@ -215,19 +242,33 @@ class TestOrtSession:
             {"arena_extend_strategy": "kSameAsRequested"},
         ]
 
-    def test_sets_device_id_for_openvino(self) -> None:
+    def test_sets_provider_options_for_openvino(self) -> None:
+        model_path = "/cache/ViT-B-32__openai/textual/model.onnx"
         os.environ["MACHINE_LEARNING_DEVICE_ID"] = "1"
 
-        session = OrtSession("ViT-B-32__openai", providers=["OpenVINOExecutionProvider"])
+        session = OrtSession(model_path, providers=["OpenVINOExecutionProvider"])
 
-        assert session.provider_options[0]["device_type"] == "GPU.1"
+        assert session.provider_options == [
+            {
+                "device_type": "GPU.1",
+                "precision": "FP32",
+                "cache_dir": "/cache/ViT-B-32__openai/textual/openvino",
+            }
+        ]
 
-    def test_sets_device_id_for_cuda(self) -> None:
+    def test_sets_provider_options_for_cuda(self) -> None:
         os.environ["MACHINE_LEARNING_DEVICE_ID"] = "1"
 
         session = OrtSession("ViT-B-32__openai", providers=["CUDAExecutionProvider"])
 
-        assert session.provider_options[0]["device_id"] == "1"
+        assert session.provider_options == [{"arena_extend_strategy": "kSameAsRequested", "device_id": "1"}]
+
+    def test_sets_provider_options_for_rocm(self) -> None:
+        os.environ["MACHINE_LEARNING_DEVICE_ID"] = "1"
+
+        session = OrtSession("ViT-B-32__openai", providers=["ROCMExecutionProvider"])
+
+        assert session.provider_options == [{"arena_extend_strategy": "kSameAsRequested", "device_id": "1"}]
 
     def test_sets_provider_options_kwarg(self) -> None:
         session = OrtSession(
@@ -328,6 +369,33 @@ class TestAnnSession:
         np_spy.assert_has_calls([mock.call(input1), mock.call(input2)])
 
 
+class TestRknnSession:
+    def test_creates_rknn_session(self, rknn_session: mock.Mock, info: mock.Mock, mocker: MockerFixture) -> None:
+        model_path = mock.MagicMock(spec=Path)
+        tpe = 1
+        mocker.patch("app.sessions.rknn.soc_name", "rk3566")
+        mocker.patch("app.sessions.rknn.is_available", True)
+        RknnSession(model_path)
+
+        rknn_session.assert_called_once_with(model_path=model_path.as_posix(), tpes=tpe, func=run_inference)
+
+        info.assert_has_calls([mock.call(f"Loaded RKNN model from {model_path} with {tpe} threads.")])
+
+    def test_run_rknn(self, rknn_session: mock.Mock, mocker: MockerFixture) -> None:
+        rknn_session.return_value.load.return_value = 123
+        np_spy = mocker.spy(np, "ascontiguousarray")
+        mocker.patch("app.sessions.rknn.soc_name", "rk3566")
+        session = RknnSession(Path("ViT-B-32__openai"))
+        [input1, input2] = [np.random.rand(1, 3, 224, 224).astype(np.float32) for _ in range(2)]
+        input_feed = {"input.1": input1, "input.2": input2}
+
+        session.run(None, input_feed)
+
+        rknn_session.return_value.put.assert_called_once_with([input1, input2])
+        np_spy.call_count == 2
+        np_spy.assert_has_calls([mock.call(input1), mock.call(input2)])
+
+
 class TestCLIP:
     embedding = np.random.rand(512).astype(np.float32)
     cache_dir = Path("test_cache")
@@ -829,9 +897,7 @@ class TestLoad:
         mock_model.clear_cache.assert_not_called()
         mock_model.load.assert_not_called()
 
-    async def test_falls_back_to_onnx_if_other_format_does_not_exist(
+    async def test_falls_back_to_onnx_if_other_format_does_not_exist(self, warning: mock.Mock) -> None:
-        self, exception: mock.Mock, warning: mock.Mock
-    ) -> None:
         mock_model = mock.Mock(spec=InferenceModel)
         mock_model.model_name = "test_model_name"
         mock_model.model_type = ModelType.VISUAL
@@ -846,8 +912,9 @@ class TestLoad:
 
         mock_model.clear_cache.assert_not_called()
         assert mock_model.load.call_count == 2
-        exception.assert_called_once_with(error)
+        warning.assert_called_once_with(
-        warning.assert_called_once_with("ARMNN is available, but model 'test_model_name' does not support it.")
+            "ARMNN is available, but model 'test_model_name' does not support it.", exc_info=error
+        )
         mock_model.model_format = ModelFormat.ONNX
 
 

machine-learning/export/.python-version

@@ -0,0 +1 @@
+3.12

machine-learning/export/Dockerfile

@@ -1,20 +0,0 @@
-FROM mambaorg/micromamba:bookworm-slim@sha256:e3797091302382ea841498bc93a7b0a50f7c1448333d5e946d2d1608d0c5f43d AS builder
-
-ENV TRANSFORMERS_CACHE=/cache \
-  PYTHONDONTWRITEBYTECODE=1 \
-  PYTHONUNBUFFERED=1 \
-  PATH="/opt/venv/bin:$PATH" \
-  PYTHONPATH=/usr/src
-
-COPY --chown=$MAMBA_USER:$MAMBA_USER conda-lock.yml /tmp/conda-lock.yml
-RUN micromamba install -y -n base -f /tmp/conda-lock.yml && \
-    micromamba remove -y -n base cxx-compiler && \
-    micromamba clean --all --yes
-
-WORKDIR /usr/src/app
-
-COPY --chown=$MAMBA_USER:$MAMBA_USER start.sh .
-COPY --chown=$MAMBA_USER:$MAMBA_USER app .
-
-ENTRYPOINT ["/usr/local/bin/_entrypoint.sh"]
-CMD ["./start.sh"]

machine-learning/export/env.dev.yaml

@@ -1,15 +0,0 @@
-name: base
-channels:
-  - conda-forge
-platforms:
-  - linux-64
-  - linux-aarch64
-dependencies:
-  - black
-  - conda-lock
-  - mypy
-  - pytest
-  - pytest-cov
-  - pytest-mock
-  - ruff
-category: dev

machine-learning/export/env.yaml

@@ -1,25 +0,0 @@
-name: base
-channels:
-  - conda-forge
-  - nvidia
-  - pytorch
-platforms:
-  - linux-64
-dependencies:
-  - cxx-compiler
-  - onnx==1.*
-  - onnxruntime==1.*
-  - open-clip-torch==2.*
-  - orjson==3.*
-  - pip
-  - python==3.11.*
-  - pytorch>=2.3
-  - rich==13.*
-  - safetensors==0.*
-  - setuptools==68.*
-  - torchvision
-  - transformers==4.*
-  - pip:
-    - multilingual-clip
-    - onnxsim
-category: main

machine-learning/export/immich_model_exporter/export.py

@@ -0,0 +1,98 @@
+from pathlib import Path
+
+import typer
+from tenacity import retry, stop_after_attempt, wait_fixed
+from typing_extensions import Annotated
+
+from .exporters.constants import DELETE_PATTERNS, SOURCE_TO_METADATA, ModelSource
+from .exporters.onnx import export as onnx_export
+from .exporters.rknn import export as rknn_export
+
+app = typer.Typer(pretty_exceptions_show_locals=False)
+
+
+def generate_readme(model_name: str, model_source: ModelSource) -> str:
+    (name, link, type) = SOURCE_TO_METADATA[model_source]
+    match model_source:
+        case ModelSource.MCLIP:
+            tags = ["immich", "clip", "multilingual"]
+        case ModelSource.OPENCLIP:
+            tags = ["immich", "clip"]
+            lowered = model_name.lower()
+            if "xlm" in lowered or "nllb" in lowered:
+                tags.append("multilingual")
+        case ModelSource.INSIGHTFACE:
+            tags = ["immich", "facial-recognition"]
+        case _:
+            raise ValueError(f"Unsupported model source {model_source}")
+
+    return f"""---
+tags:
+{" - " + "\n - ".join(tags)}
+---
+# Model Description
+
+This repo contains ONNX exports for the associated {type} model by {name}. See the [{name}]({link}) repo for more info.
+
+This repo is specifically intended for use with [Immich](https://immich.app/), a self-hosted photo library.
+"""
+
+
+@app.command()
+def main(
+    model_name: str,
+    model_source: ModelSource,
+    output_dir: Path = Path("./models"),
+    no_cache: bool = False,
+    hf_organization: str = "immich-app",
+    hf_auth_token: Annotated[str | None, typer.Option(envvar="HF_AUTH_TOKEN")] = None,
+) -> None:
+    hf_model_name = model_name.split("/")[-1]
+    hf_model_name = hf_model_name.replace("xlm-roberta-large", "XLM-Roberta-Large")
+    hf_model_name = hf_model_name.replace("xlm-roberta-base", "XLM-Roberta-Base")
+    output_dir = output_dir / hf_model_name
+    match model_source:
+        case ModelSource.MCLIP | ModelSource.OPENCLIP:
+            output_dir.mkdir(parents=True, exist_ok=True)
+            onnx_export(model_name, model_source, output_dir, no_cache=no_cache)
+        case ModelSource.INSIGHTFACE:
+            from huggingface_hub import snapshot_download
+
+            # TODO: start from insightface dump instead of downloading from HF
+            snapshot_download(f"immich-app/{hf_model_name}", local_dir=output_dir)
+        case _:
+            raise ValueError(f"Unsupported model source {model_source}")
+
+    try:
+        rknn_export(output_dir, no_cache=no_cache)
+    except Exception as e:
+        print(f"Failed to export model {model_name} to rknn: {e}")
+        (output_dir / "rknpu").unlink(missing_ok=True)
+
+    readme_path = output_dir / "README.md"
+    if no_cache or not readme_path.exists():
+        with open(readme_path, "w") as f:
+            f.write(generate_readme(model_name, model_source))
+
+    if hf_auth_token is not None:
+        from huggingface_hub import create_repo, upload_folder
+
+        repo_id = f"{hf_organization}/{hf_model_name}"
+
+        @retry(stop=stop_after_attempt(5), wait=wait_fixed(5))
+        def upload_model() -> None:
+            create_repo(repo_id, exist_ok=True, token=hf_auth_token)
+            upload_folder(
+                repo_id=repo_id,
+                folder_path=output_dir,
+                # remote repo files to be deleted before uploading
+                # deletion is in the same commit as the upload, so it's atomic
+                delete_patterns=DELETE_PATTERNS,
+                token=hf_auth_token,
+            )
+
+        upload_model()
+
+
+if __name__ == "__main__":
+    typer.run(main)

machine-learning/export/immich_model_exporter/exporters/constants.py

@@ -0,0 +1,42 @@
+from enum import StrEnum
+from typing import NamedTuple
+
+
+class ModelSource(StrEnum):
+    INSIGHTFACE = "insightface"
+    MCLIP = "mclip"
+    OPENCLIP = "openclip"
+
+
+class SourceMetadata(NamedTuple):
+    name: str
+    link: str
+    type: str
+
+
+SOURCE_TO_METADATA = {
+    ModelSource.MCLIP: SourceMetadata("M-CLIP", "https://huggingface.co/M-CLIP", "CLIP"),
+    ModelSource.OPENCLIP: SourceMetadata("OpenCLIP", "https://github.com/mlfoundations/open_clip", "CLIP"),
+    ModelSource.INSIGHTFACE: SourceMetadata(
+        "InsightFace", "https://github.com/deepinsight/insightface/tree/master", "facial recognition"
+    ),
+}
+
+RKNN_SOCS = ["rk3566", "rk3568", "rk3576", "rk3588"]
+
+
+# glob to delete old UUID blobs when reuploading models
+_uuid_char = "[a-fA-F0-9]"
+_uuid_glob = _uuid_char * 8 + "-" + _uuid_char * 4 + "-" + _uuid_char * 4 + "-" + _uuid_char * 4 + "-" + _uuid_char * 12
+DELETE_PATTERNS = [
+    "**/*onnx*",
+    "**/Constant*",
+    "**/*.weight",
+    "**/*.bias",
+    "**/*.proj",
+    "**/*in_proj_bias",
+    "**/*.npy",
+    "**/*.latent",
+    "**/*.pos_embed",
+    f"**/{_uuid_glob}",
+]

machine-learning/export/immich_model_exporter/exporters/onnx/__init__.py

@@ -0,0 +1,20 @@
+from pathlib import Path
+
+from ..constants import ModelSource
+from .models import mclip, openclip
+
+
+def export(
+    model_name: str, model_source: ModelSource, output_dir: Path, opset_version: int = 19, no_cache: bool = False
+) -> None:
+    visual_dir = output_dir / "visual"
+    textual_dir = output_dir / "textual"
+    match model_source:
+        case ModelSource.MCLIP:
+            mclip.to_onnx(model_name, opset_version, visual_dir, textual_dir, no_cache=no_cache)
+        case ModelSource.OPENCLIP:
+            name, _, pretrained = model_name.partition("__")
+            config = openclip.OpenCLIPModelConfig(name, pretrained)
+            openclip.to_onnx(config, opset_version, visual_dir, textual_dir, no_cache=no_cache)
+        case _:
+            raise ValueError(f"Unsupported model source {model_source}")

machine-learning/export/immich_model_exporter/exporters/onnx/models/mclip.py

@@ -1,11 +1,6 @@
-import os
-import tempfile
 import warnings
 from pathlib import Path
-
+from typing import Any
-import torch
-from multilingual_clip.pt_multilingual_clip import MultilingualCLIP
-from transformers import AutoTokenizer
 
 from .openclip import OpenCLIPModelConfig
 from .openclip import to_onnx as openclip_to_onnx
@@ -21,25 +16,40 @@ _MCLIP_TO_OPENCLIP = {
 
 def to_onnx(
     model_name: str,
+    opset_version: int,
     output_dir_visual: Path | str,
     output_dir_textual: Path | str,
+    no_cache: bool = False,
 ) -> tuple[Path, Path]:
     textual_path = get_model_path(output_dir_textual)
-    with tempfile.TemporaryDirectory() as tmpdir:
+    if no_cache or not textual_path.exists():
-        model = MultilingualCLIP.from_pretrained(model_name, cache_dir=os.environ.get("CACHE_DIR", tmpdir))
+        import torch
+        from multilingual_clip.pt_multilingual_clip import MultilingualCLIP
+        from transformers import AutoTokenizer
+
+        torch.backends.mha.set_fastpath_enabled(False)
+
+        model = MultilingualCLIP.from_pretrained(model_name)
         AutoTokenizer.from_pretrained(model_name).save_pretrained(output_dir_textual)
 
         model.eval()
         for param in model.parameters():
             param.requires_grad_(False)
 
-        export_text_encoder(model, textual_path)
+        _export_text_encoder(model, textual_path, opset_version)
-        visual_path, _ = openclip_to_onnx(_MCLIP_TO_OPENCLIP[model_name], output_dir_visual)
+    else:
+        print(f"Model {textual_path} already exists, skipping")
+    visual_path, _ = openclip_to_onnx(
+        _MCLIP_TO_OPENCLIP[model_name], opset_version, output_dir_visual, no_cache=no_cache
+    )
     assert visual_path is not None, "Visual model export failed"
     return visual_path, textual_path
 
 
-def export_text_encoder(model: MultilingualCLIP, output_path: Path | str) -> None:
+def _export_text_encoder(model: Any, output_path: Path | str, opset_version: int) -> None:
+    import torch
+    from multilingual_clip.pt_multilingual_clip import MultilingualCLIP
+
     output_path = Path(output_path)
 
     def forward(self: MultilingualCLIP, input_ids: torch.Tensor, attention_mask: torch.Tensor) -> torch.Tensor:
@@ -61,7 +71,7 @@ def export_text_encoder(model: MultilingualCLIP, output_path: Path | str) -> Non
             output_path.as_posix(),
             input_names=["input_ids", "attention_mask"],
             output_names=["embedding"],
-            opset_version=17,
+            opset_version=opset_version,
             # dynamic_axes={
             #     "input_ids": {0: "batch_size", 1: "sequence_length"},
             #     "attention_mask": {0: "batch_size", 1: "sequence_length"},

machine-learning/export/immich_model_exporter/exporters/onnx/models/openclip.py

@@ -0,0 +1,153 @@
+import warnings
+from dataclasses import dataclass
+from functools import cached_property
+from pathlib import Path
+from typing import Any
+
+from .util import get_model_path, save_config
+
+
+@dataclass
+class OpenCLIPModelConfig:
+    name: str
+    pretrained: str
+
+    @cached_property
+    def model_config(self) -> dict[str, Any]:
+        import open_clip
+
+        config: dict[str, Any] | None = open_clip.get_model_config(self.name)
+        if config is None:
+            raise ValueError(f"Unknown model {self.name}")
+        return config
+
+    @property
+    def image_size(self) -> int:
+        image_size: int = self.model_config["vision_cfg"]["image_size"]
+        return image_size
+
+    @property
+    def sequence_length(self) -> int:
+        context_length: int = self.model_config["text_cfg"].get("context_length", 77)
+        return context_length
+
+
+def to_onnx(
+    model_cfg: OpenCLIPModelConfig,
+    opset_version: int,
+    output_dir_visual: Path | str | None = None,
+    output_dir_textual: Path | str | None = None,
+    no_cache: bool = False,
+) -> tuple[Path | None, Path | None]:
+    visual_path = None
+    textual_path = None
+    if output_dir_visual is not None:
+        output_dir_visual = Path(output_dir_visual)
+        visual_path = get_model_path(output_dir_visual)
+
+    if output_dir_textual is not None:
+        output_dir_textual = Path(output_dir_textual)
+        textual_path = get_model_path(output_dir_textual)
+
+    if not no_cache and (
+        (textual_path is None or textual_path.exists()) and (visual_path is None or visual_path.exists())
+    ):
+        print(f"Models {textual_path} and {visual_path} already exist, skipping")
+        return visual_path, textual_path
+
+    import open_clip
+    import torch
+    from transformers import AutoTokenizer
+
+    torch.backends.mha.set_fastpath_enabled(False)
+
+    model = open_clip.create_model(
+        model_cfg.name,
+        pretrained=model_cfg.pretrained,
+        jit=False,
+        require_pretrained=True,
+    )
+
+    text_vision_cfg = open_clip.get_model_config(model_cfg.name)
+
+    model.eval()
+    for param in model.parameters():
+        param.requires_grad_(False)
+
+    if visual_path is not None and output_dir_visual is not None:
+        if no_cache or not visual_path.exists():
+            save_config(
+                open_clip.get_model_preprocess_cfg(model),
+                output_dir_visual / "preprocess_cfg.json",
+            )
+            save_config(text_vision_cfg, output_dir_visual.parent / "config.json")
+            _export_image_encoder(model, model_cfg, visual_path, opset_version)
+        else:
+            print(f"Model {visual_path} already exists, skipping")
+
+    if textual_path is not None and output_dir_textual is not None:
+        if no_cache or not textual_path.exists():
+            tokenizer_name = text_vision_cfg["text_cfg"].get("hf_tokenizer_name", "openai/clip-vit-base-patch32")
+            AutoTokenizer.from_pretrained(tokenizer_name).save_pretrained(output_dir_textual)
+            _export_text_encoder(model, model_cfg, textual_path, opset_version)
+        else:
+            print(f"Model {textual_path} already exists, skipping")
+    return visual_path, textual_path
+
+
+def _export_image_encoder(
+    model: Any, model_cfg: OpenCLIPModelConfig, output_path: Path | str, opset_version: int
+) -> None:
+    import torch
+
+    output_path = Path(output_path)
+
+    def encode_image(image: torch.Tensor) -> torch.Tensor:
+        output = model.encode_image(image, normalize=True)
+        assert isinstance(output, torch.Tensor)
+        return output
+
+    model.forward = encode_image
+
+    args = (torch.randn(1, 3, model_cfg.image_size, model_cfg.image_size),)
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", UserWarning)
+        torch.onnx.export(
+            model,
+            args,
+            output_path.as_posix(),
+            input_names=["image"],
+            output_names=["embedding"],
+            opset_version=opset_version,
+            # dynamic_axes={"image": {0: "batch_size"}},
+        )
+
+
+def _export_text_encoder(
+    model: Any, model_cfg: OpenCLIPModelConfig, output_path: Path | str, opset_version: int
+) -> None:
+    import torch
+
+    output_path = Path(output_path)
+
+    def encode_text(text: torch.Tensor) -> torch.Tensor:
+        output = model.encode_text(text, normalize=True)
+        assert isinstance(output, torch.Tensor)
+        return output
+
+    model.forward = encode_text
+
+    args = (torch.ones(1, model_cfg.sequence_length, dtype=torch.int32),)
+
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", UserWarning)
+        torch.onnx.export(
+            model,
+            args,
+            output_path.as_posix(),
+            input_names=["text"],
+            output_names=["embedding"],
+            opset_version=opset_version,
+            # dynamic_axes={"text": {0: "batch_size"}},
+        )

machine-learning/export/immich_model_exporter/exporters/rknn.py

@@ -0,0 +1,96 @@
+from pathlib import Path
+
+from .constants import RKNN_SOCS
+
+
+def _export_platform(
+    model_dir: Path,
+    target_platform: str,
+    inputs: list[str] | None = None,
+    input_size_list: list[list[int]] | None = None,
+    fuse_matmul_softmax_matmul_to_sdpa: bool = True,
+    no_cache: bool = False,
+) -> None:
+    from rknn.api import RKNN
+
+    input_path = model_dir / "model.onnx"
+    output_path = model_dir / "rknpu" / target_platform / "model.rknn"
+    if not no_cache and output_path.exists():
+        print(f"Model {input_path} already exists at {output_path}, skipping")
+        return
+
+    print(f"Exporting model {input_path} to {output_path}")
+
+    rknn = RKNN(verbose=False)
+
+    rknn.config(
+        target_platform=target_platform,
+        disable_rules=["fuse_matmul_softmax_matmul_to_sdpa"] if not fuse_matmul_softmax_matmul_to_sdpa else [],
+        enable_flash_attention=False,
+        model_pruning=True,
+    )
+    ret = rknn.load_onnx(model=input_path.as_posix(), inputs=inputs, input_size_list=input_size_list)
+
+    if ret != 0:
+        raise RuntimeError("Load failed!")
+
+    ret = rknn.build(do_quantization=False)
+
+    if ret != 0:
+        raise RuntimeError("Build failed!")
+
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    ret = rknn.export_rknn(output_path.as_posix())
+    if ret != 0:
+        raise RuntimeError("Export rknn model failed!")
+
+
+def _export_platforms(
+    model_dir: Path,
+    inputs: list[str] | None = None,
+    input_size_list: list[list[int]] | None = None,
+    no_cache: bool = False,
+) -> None:
+    fuse_matmul_softmax_matmul_to_sdpa = True
+    for soc in RKNN_SOCS:
+        try:
+            _export_platform(
+                model_dir,
+                soc,
+                inputs=inputs,
+                input_size_list=input_size_list,
+                fuse_matmul_softmax_matmul_to_sdpa=fuse_matmul_softmax_matmul_to_sdpa,
+                no_cache=no_cache,
+            )
+        except Exception as e:
+            print(f"Failed to export model for {soc}: {e}")
+            if "inputs or 'outputs' must be set" in str(e):
+                print("Retrying without fuse_matmul_softmax_matmul_to_sdpa")
+                fuse_matmul_softmax_matmul_to_sdpa = False
+                _export_platform(
+                    model_dir,
+                    soc,
+                    inputs=inputs,
+                    input_size_list=input_size_list,
+                    fuse_matmul_softmax_matmul_to_sdpa=fuse_matmul_softmax_matmul_to_sdpa,
+                    no_cache=no_cache,
+                )
+
+
+def export(model_dir: Path, no_cache: bool = False) -> None:
+    textual = model_dir / "textual"
+    visual = model_dir / "visual"
+    detection = model_dir / "detection"
+    recognition = model_dir / "recognition"
+
+    if textual.is_dir():
+        _export_platforms(textual, no_cache=no_cache)
+
+    if visual.is_dir():
+        _export_platforms(visual, no_cache=no_cache)
+
+    if detection.is_dir():
+        _export_platforms(detection, inputs=["input.1"], input_size_list=[[1, 3, 640, 640]], no_cache=no_cache)
+
+    if recognition.is_dir():
+        _export_platforms(recognition, inputs=["input.1"], input_size_list=[[1, 3, 112, 112]], no_cache=no_cache)

machine-learning/export/immich_model_exporter/run.py

@@ -0,0 +1,88 @@
+import subprocess
+
+from exporters.constants import ModelSource
+
+mclip = [
+    "M-CLIP/LABSE-Vit-L-14",
+    "M-CLIP/XLM-Roberta-Large-Vit-B-16Plus",
+    "M-CLIP/XLM-Roberta-Large-Vit-B-32",
+    "M-CLIP/XLM-Roberta-Large-Vit-L-14",
+]
+
+openclip = [
+    "RN101__openai",
+    "RN101__yfcc15m",
+    "RN50__cc12m",
+    "RN50__openai",
+    "RN50__yfcc15m",
+    "RN50x16__openai",
+    "RN50x4__openai",
+    "RN50x64__openai",
+    "ViT-B-16-SigLIP-256__webli",
+    "ViT-B-16-SigLIP-384__webli",
+    "ViT-B-16-SigLIP-512__webli",
+    "ViT-B-16-SigLIP-i18n-256__webli",
+    "ViT-B-16-SigLIP2__webli",
+    "ViT-B-16-SigLIP__webli",
+    "ViT-B-16-plus-240__laion400m_e31",
+    "ViT-B-16-plus-240__laion400m_e32",
+    "ViT-B-16__laion400m_e31",
+    "ViT-B-16__laion400m_e32",
+    "ViT-B-16__openai",
+    "ViT-B-32-SigLIP2-256__webli",
+    "ViT-B-32__laion2b-s34b-b79k",
+    "ViT-B-32__laion2b_e16",
+    "ViT-B-32__laion400m_e31",
+    "ViT-B-32__laion400m_e32",
+    "ViT-B-32__openai",
+    "ViT-H-14-378-quickgelu__dfn5b",
+    "ViT-H-14-quickgelu__dfn5b",
+    "ViT-H-14__laion2b-s32b-b79k",
+    "ViT-L-14-336__openai",
+    "ViT-L-14-quickgelu__dfn2b",
+    "ViT-L-14__laion2b-s32b-b82k",
+    "ViT-L-14__laion400m_e31",
+    "ViT-L-14__laion400m_e32",
+    "ViT-L-14__openai",
+    "ViT-L-16-SigLIP-256__webli",
+    "ViT-L-16-SigLIP-384__webli",
+    "ViT-L-16-SigLIP2-256__webli",
+    "ViT-L-16-SigLIP2-384__webli",
+    "ViT-L-16-SigLIP2-512__webli",
+    "ViT-SO400M-14-SigLIP-384__webli",
+    "ViT-SO400M-14-SigLIP2-378__webli",
+    "ViT-SO400M-14-SigLIP2__webli",
+    "ViT-SO400M-16-SigLIP2-256__webli",
+    "ViT-SO400M-16-SigLIP2-384__webli",
+    "ViT-SO400M-16-SigLIP2-512__webli",
+    "ViT-gopt-16-SigLIP2-256__webli",
+    "ViT-gopt-16-SigLIP2-384__webli",
+    "nllb-clip-base-siglip__mrl",
+    "nllb-clip-base-siglip__v1",
+    "nllb-clip-large-siglip__mrl",
+    "nllb-clip-large-siglip__v1",
+    "xlm-roberta-base-ViT-B-32__laion5b_s13b_b90k",
+    "xlm-roberta-large-ViT-H-14__frozen_laion5b_s13b_b90k",
+]
+
+insightface = [
+    "antelopev2",
+    "buffalo_l",
+    "buffalo_m",
+    "buffalo_s",
+]
+
+
+def export_models(models: list[str], source: ModelSource) -> None:
+    for model in models:
+        try:
+            print(f"Exporting model {model}")
+            subprocess.check_call(["python", "-m", "immich_model_exporter.export", model, source])
+        except Exception as e:
+            print(f"Failed to export model {model}: {e}")
+
+
+if __name__ == "__main__":
+    export_models(mclip, ModelSource.MCLIP)
+    export_models(openclip, ModelSource.OPENCLIP)
+    export_models(insightface, ModelSource.INSIGHTFACE)

machine-learning/export/models/openclip.py

@@ -1,114 +0,0 @@
-import os
-import tempfile
-import warnings
-from dataclasses import dataclass, field
-from pathlib import Path
-
-import open_clip
-import torch
-from transformers import AutoTokenizer
-
-from .util import get_model_path, save_config
-
-
-@dataclass
-class OpenCLIPModelConfig:
-    name: str
-    pretrained: str
-    image_size: int = field(init=False)
-    sequence_length: int = field(init=False)
-
-    def __post_init__(self) -> None:
-        open_clip_cfg = open_clip.get_model_config(self.name)
-        if open_clip_cfg is None:
-            raise ValueError(f"Unknown model {self.name}")
-        self.image_size = open_clip_cfg["vision_cfg"]["image_size"]
-        self.sequence_length = open_clip_cfg["text_cfg"].get("context_length", 77)
-
-
-def to_onnx(
-    model_cfg: OpenCLIPModelConfig,
-    output_dir_visual: Path | str | None = None,
-    output_dir_textual: Path | str | None = None,
-) -> tuple[Path | None, Path | None]:
-    visual_path = None
-    textual_path = None
-    with tempfile.TemporaryDirectory() as tmpdir:
-        model = open_clip.create_model(
-            model_cfg.name,
-            pretrained=model_cfg.pretrained,
-            jit=False,
-            cache_dir=os.environ.get("CACHE_DIR", tmpdir),
-            require_pretrained=True,
-        )
-
-        text_vision_cfg = open_clip.get_model_config(model_cfg.name)
-
-        model.eval()
-        for param in model.parameters():
-            param.requires_grad_(False)
-
-        if output_dir_visual is not None:
-            output_dir_visual = Path(output_dir_visual)
-            visual_path = get_model_path(output_dir_visual)
-
-            save_config(open_clip.get_model_preprocess_cfg(model), output_dir_visual / "preprocess_cfg.json")
-            save_config(text_vision_cfg, output_dir_visual.parent / "config.json")
-            export_image_encoder(model, model_cfg, visual_path)
-
-        if output_dir_textual is not None:
-            output_dir_textual = Path(output_dir_textual)
-            textual_path = get_model_path(output_dir_textual)
-
-            tokenizer_name = text_vision_cfg["text_cfg"].get("hf_tokenizer_name", "openai/clip-vit-base-patch32")
-            AutoTokenizer.from_pretrained(tokenizer_name).save_pretrained(output_dir_textual)
-            export_text_encoder(model, model_cfg, textual_path)
-    return visual_path, textual_path
-
-
-def export_image_encoder(model: open_clip.CLIP, model_cfg: OpenCLIPModelConfig, output_path: Path | str) -> None:
-    output_path = Path(output_path)
-
-    def encode_image(image: torch.Tensor) -> torch.Tensor:
-        output = model.encode_image(image, normalize=True)
-        assert isinstance(output, torch.Tensor)
-        return output
-
-    args = (torch.randn(1, 3, model_cfg.image_size, model_cfg.image_size),)
-    traced = torch.jit.trace(encode_image, args)  # type: ignore[no-untyped-call]
-
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", UserWarning)
-        torch.onnx.export(
-            traced,
-            args,
-            output_path.as_posix(),
-            input_names=["image"],
-            output_names=["embedding"],
-            opset_version=17,
-            # dynamic_axes={"image": {0: "batch_size"}},
-        )
-
-
-def export_text_encoder(model: open_clip.CLIP, model_cfg: OpenCLIPModelConfig, output_path: Path | str) -> None:
-    output_path = Path(output_path)
-
-    def encode_text(text: torch.Tensor) -> torch.Tensor:
-        output = model.encode_text(text, normalize=True)
-        assert isinstance(output, torch.Tensor)
-        return output
-
-    args = (torch.ones(1, model_cfg.sequence_length, dtype=torch.int32),)
-    traced = torch.jit.trace(encode_text, args)  # type: ignore[no-untyped-call]
-
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", UserWarning)
-        torch.onnx.export(
-            traced,
-            args,
-            output_path.as_posix(),
-            input_names=["text"],
-            output_names=["embedding"],
-            opset_version=17,
-            # dynamic_axes={"text": {0: "batch_size"}},
-        )

machine-learning/export/models/optimize.py

@@ -1,49 +0,0 @@
-from pathlib import Path
-
-import onnx
-import onnxruntime as ort
-import onnxsim
-
-
-def save_onnx(model: onnx.ModelProto, output_path: Path | str) -> None:
-    try:
-        onnx.save(model, output_path)
-    except ValueError as e:
-        if "The proto size is larger than the 2 GB limit." in str(e):
-            onnx.save(model, output_path, save_as_external_data=True, size_threshold=1_000_000)
-        else:
-            raise e
-
-
-def optimize_onnxsim(model_path: Path | str, output_path: Path | str) -> None:
-    model_path = Path(model_path)
-    output_path = Path(output_path)
-    model = onnx.load(model_path.as_posix())
-    model, check = onnxsim.simplify(model)
-    assert check, "Simplified ONNX model could not be validated"
-    for file in model_path.parent.iterdir():
-        if file.name.startswith("Constant") or "onnx" in file.name or file.suffix == ".weight":
-            file.unlink()
-    save_onnx(model, output_path)
-
-
-def optimize_ort(
-    model_path: Path | str,
-    output_path: Path | str,
-    level: ort.GraphOptimizationLevel = ort.GraphOptimizationLevel.ORT_ENABLE_BASIC,
-) -> None:
-    model_path = Path(model_path)
-    output_path = Path(output_path)
-
-    sess_options = ort.SessionOptions()
-    sess_options.graph_optimization_level = level
-    sess_options.optimized_model_filepath = output_path.as_posix()
-
-    ort.InferenceSession(model_path.as_posix(), providers=["CPUExecutionProvider"], sess_options=sess_options)
-
-
-def optimize(model_path: Path | str) -> None:
-    model_path = Path(model_path)
-
-    optimize_ort(model_path, model_path)
-    optimize_onnxsim(model_path, model_path)

machine-learning/export/pyproject.toml

@@ -0,0 +1,67 @@
+[project]
+name = "immich_model_exporter"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10, <4.0"
+dependencies = [
+  "huggingface-hub>=0.29.3",
+  "multilingual-clip>=1.0.10",
+  "onnx>=1.14.1",
+  "onnxruntime>=1.16.0",
+  "open-clip-torch>=2.31.0",
+  "typer>=0.15.2",
+  "rknn-toolkit2>=2.3.0",
+  "transformers>=4.49.0",
+  "tenacity>=9.0.0",
+]
+
+[dependency-groups]
+dev = ["black>=23.3.0", "mypy>=1.3.0", "ruff>=0.0.272"]
+
+[tool.uv]
+override-dependencies = [
+  "onnx>=1.16.0,<2",
+  "onnxruntime>=1.18.2,<2",
+  "torch>=2.4",
+  "torchvision>=0.21",
+]
+
+[tool.uv.sources]
+torch = [{ index = "pytorch-cpu" }]
+torchvision = [{ index = "pytorch-cpu" }]
+
+[[tool.uv.index]]
+name = "pytorch-cpu"
+url = "https://download.pytorch.org/whl/cpu"
+explicit = true
+
+[tool.hatch.build.targets.sdist]
+include = ["immich_model_exporter"]
+
+[tool.hatch.build.targets.wheel]
+include = ["immich_model_exporter"]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.mypy]
+python_version = "3.12"
+follow_imports = "silent"
+warn_redundant_casts = true
+disallow_any_generics = true
+check_untyped_defs = true
+disallow_untyped_defs = true
+ignore_missing_imports = true
+
+[tool.ruff]
+line-length = 120
+target-version = "py312"
+
+[tool.ruff.lint]
+select = ["E", "F", "I"]
+
+[tool.black]
+line-length = 120
+target-version = ['py312']

machine-learning/export/run.py

@@ -1,113 +0,0 @@
-import gc
-import os
-from pathlib import Path
-from tempfile import TemporaryDirectory
-
-import torch
-from huggingface_hub import create_repo, upload_folder
-from models import mclip, openclip
-from models.optimize import optimize
-from rich.progress import Progress
-
-models = [
-    "M-CLIP/LABSE-Vit-L-14",
-    "M-CLIP/XLM-Roberta-Large-Vit-B-16Plus",
-    "M-CLIP/XLM-Roberta-Large-Vit-B-32",
-    "M-CLIP/XLM-Roberta-Large-Vit-L-14",
-    "RN101::openai",
-    "RN101::yfcc15m",
-    "RN50::cc12m",
-    "RN50::openai",
-    "RN50::yfcc15m",
-    "RN50x16::openai",
-    "RN50x4::openai",
-    "RN50x64::openai",
-    "ViT-B-16-SigLIP-256::webli",
-    "ViT-B-16-SigLIP-384::webli",
-    "ViT-B-16-SigLIP-512::webli",
-    "ViT-B-16-SigLIP-i18n-256::webli",
-    "ViT-B-16-SigLIP::webli",
-    "ViT-B-16-plus-240::laion400m_e31",
-    "ViT-B-16-plus-240::laion400m_e32",
-    "ViT-B-16::laion400m_e31",
-    "ViT-B-16::laion400m_e32",
-    "ViT-B-16::openai",
-    "ViT-B-32::laion2b-s34b-b79k",
-    "ViT-B-32::laion2b_e16",
-    "ViT-B-32::laion400m_e31",
-    "ViT-B-32::laion400m_e32",
-    "ViT-B-32::openai",
-    "ViT-H-14-378-quickgelu::dfn5b",
-    "ViT-H-14-quickgelu::dfn5b",
-    "ViT-H-14::laion2b-s32b-b79k",
-    "ViT-L-14-336::openai",
-    "ViT-L-14-quickgelu::dfn2b",
-    "ViT-L-14::laion2b-s32b-b82k",
-    "ViT-L-14::laion400m_e31",
-    "ViT-L-14::laion400m_e32",
-    "ViT-L-14::openai",
-    "ViT-L-16-SigLIP-256::webli",
-    "ViT-L-16-SigLIP-384::webli",
-    "ViT-SO400M-14-SigLIP-384::webli",
-    "ViT-g-14::laion2b-s12b-b42k",
-    "nllb-clip-base-siglip::mrl",
-    "nllb-clip-base-siglip::v1",
-    "nllb-clip-large-siglip::mrl",
-    "nllb-clip-large-siglip::v1",
-    "xlm-roberta-base-ViT-B-32::laion5b_s13b_b90k",
-    "xlm-roberta-large-ViT-H-14::frozen_laion5b_s13b_b90k",
-]
-
-# glob to delete old UUID blobs when reuploading models
-uuid_char = "[a-fA-F0-9]"
-uuid_glob = uuid_char * 8 + "-" + uuid_char * 4 + "-" + uuid_char * 4 + "-" + uuid_char * 4 + "-" + uuid_char * 12
-
-# remote repo files to be deleted before uploading
-# deletion is in the same commit as the upload, so it's atomic
-delete_patterns = ["**/*onnx*", "**/Constant*", "**/*.weight", "**/*.bias", f"**/{uuid_glob}"]
-
-with Progress() as progress:
-    task = progress.add_task("[green]Exporting models...", total=len(models))
-    token = os.environ.get("HF_AUTH_TOKEN")
-    torch.backends.mha.set_fastpath_enabled(False)
-    with TemporaryDirectory() as tmp:
-        tmpdir = Path(tmp)
-        for model in models:
-            model_name = model.split("/")[-1].replace("::", "__")
-            hf_model_name = model_name.replace("xlm-roberta-large", "XLM-Roberta-Large")
-            hf_model_name = model_name.replace("xlm-roberta-base", "XLM-Roberta-Base")
-            config_path = tmpdir / model_name / "config.json"
-
-            def export() -> None:
-                progress.update(task, description=f"[green]Exporting {hf_model_name}")
-                visual_dir = tmpdir / hf_model_name / "visual"
-                textual_dir = tmpdir / hf_model_name / "textual"
-                if model.startswith("M-CLIP"):
-                    visual_path, textual_path = mclip.to_onnx(model, visual_dir, textual_dir)
-                else:
-                    name, _, pretrained = model_name.partition("__")
-                    config = openclip.OpenCLIPModelConfig(name, pretrained)
-                    visual_path, textual_path = openclip.to_onnx(config, visual_dir, textual_dir)
-                progress.update(task, description=f"[green]Optimizing {hf_model_name} (visual)")
-                optimize(visual_path)
-                progress.update(task, description=f"[green]Optimizing {hf_model_name} (textual)")
-                optimize(textual_path)
-
-                gc.collect()
-
-            def upload() -> None:
-                progress.update(task, description=f"[yellow]Uploading {hf_model_name}")
-                repo_id = f"immich-app/{hf_model_name}"
-
-                create_repo(repo_id, exist_ok=True)
-                upload_folder(
-                    repo_id=repo_id,
-                    folder_path=tmpdir / hf_model_name,
-                    delete_patterns=delete_patterns,
-                    token=token,
-                )
-
-            export()
-            if token is not None:
-                upload()
-            progress.update(task, advance=1)

machine-learning/patches/0001-disable-rocm-conv-algo-caching.patch

@@ -0,0 +1,179 @@
+commit 16839b58d9b3c3162a67ce5d776b36d4d24e801f
+Author: mertalev <101130780+mertalev@users.noreply.github.com>
+Date:   Wed Mar 5 11:25:38 2025 -0500
+
+    disable algo caching (attributed to @dmnieto in https://github.com/microsoft/onnxruntime/pull/19567)
+
+diff --git a/onnxruntime/core/providers/rocm/nn/conv.cc b/onnxruntime/core/providers/rocm/nn/conv.cc
+index d7f47d07a8..4060a2af52 100644
+--- a/onnxruntime/core/providers/rocm/nn/conv.cc
++++ b/onnxruntime/core/providers/rocm/nn/conv.cc
+@@ -127,7 +127,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
+
+     if (w_dims_changed) {
+       s_.last_w_dims = gsl::make_span(w_dims);
+-      s_.cached_benchmark_fwd_results.clear();
+     }
+
+     ORT_RETURN_IF_ERROR(conv_attrs_.ValidateInputShape(X->Shape(), W->Shape(), channels_last, channels_last));
+@@ -277,35 +276,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
+       HIP_CALL_THROW(hipMalloc(&s_.b_zero, malloc_size));
+       HIP_CALL_THROW(hipMemsetAsync(s_.b_zero, 0, malloc_size, Stream(context)));
+     }
+-
+-    if (!s_.cached_benchmark_fwd_results.contains(x_dims_miopen)) {
+-      miopenConvAlgoPerf_t perf;
+-      int algo_count = 1;
+-      const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
+-      static constexpr int num_algos = MIOPEN_CONVOLUTION_FWD_ALGO_COUNT;
+-      size_t max_ws_size = rocm_ep->GetMiopenConvUseMaxWorkspace() ? GetMaxWorkspaceSize(GetMiopenHandle(context), s_, kAllAlgos, num_algos, rocm_ep->GetDeviceId())
+-                                                                   : AlgoSearchWorkspaceSize;
+-      IAllocatorUniquePtr<void> algo_search_workspace = GetTransientScratchBuffer<void>(max_ws_size);
+-      MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionForwardAlgorithm(
+-          GetMiopenHandle(context),
+-          s_.x_tensor,
+-          s_.x_data,
+-          s_.w_desc,
+-          s_.w_data,
+-          s_.conv_desc,
+-          s_.y_tensor,
+-          s_.y_data,
+-          1,            // requestedAlgoCount
+-          &algo_count,  // returnedAlgoCount
+-          &perf,
+-          algo_search_workspace.get(),
+-          max_ws_size,
+-          false));  // Do not do exhaustive algo search.
+-      s_.cached_benchmark_fwd_results.insert(x_dims_miopen, {perf.fwd_algo, perf.memory});
+-    }
+-    const auto& perf = s_.cached_benchmark_fwd_results.at(x_dims_miopen);
+-    s_.fwd_algo = perf.fwd_algo;
+-    s_.workspace_bytes = perf.memory;
+   } else {
+     // set Y
+     s_.Y = context->Output(0, TensorShape(s_.y_dims));
+@@ -319,6 +289,31 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
+       s_.y_data = reinterpret_cast<HipT*>(s_.Y->MutableData<T>());
+     }
+   }
++
++  miopenConvAlgoPerf_t perf;
++  int algo_count = 1;
++  const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
++  static constexpr int num_algos = MIOPEN_CONVOLUTION_FWD_ALGO_COUNT;
++  size_t max_ws_size = rocm_ep->GetMiopenConvUseMaxWorkspace() ? GetMaxWorkspaceSize(GetMiopenHandle(context), s_, kAllAlgos, num_algos, rocm_ep->GetDeviceId())
++                                                                : AlgoSearchWorkspaceSize;
++  IAllocatorUniquePtr<void> algo_search_workspace = GetTransientScratchBuffer<void>(max_ws_size);
++  MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionForwardAlgorithm(
++      GetMiopenHandle(context),
++      s_.x_tensor,
++      s_.x_data,
++      s_.w_desc,
++      s_.w_data,
++      s_.conv_desc,
++      s_.y_tensor,
++      s_.y_data,
++      1,            // requestedAlgoCount
++      &algo_count,  // returnedAlgoCount
++      &perf,
++      algo_search_workspace.get(),
++      max_ws_size,
++      false));  // Do not do exhaustive algo search.
++  s_.fwd_algo = perf.fwd_algo;
++  s_.workspace_bytes = perf.memory;
+   return Status::OK();
+ }
+
+diff --git a/onnxruntime/core/providers/rocm/nn/conv.h b/onnxruntime/core/providers/rocm/nn/conv.h
+index bc9846203e..d54218f258 100644
+--- a/onnxruntime/core/providers/rocm/nn/conv.h
++++ b/onnxruntime/core/providers/rocm/nn/conv.h
+@@ -108,9 +108,6 @@ class lru_unordered_map {
+   list_type lru_list_;
+ };
+
+-// cached miopen descriptors
+-constexpr size_t MAX_CACHED_ALGO_PERF_RESULTS = 10000;
+-
+ template <typename AlgoPerfType>
+ struct MiopenConvState {
+   // if x/w dims changed, update algo and miopenTensors
+@@ -148,9 +145,6 @@ struct MiopenConvState {
+     decltype(AlgoPerfType().memory) memory;
+   };
+
+-  lru_unordered_map<TensorShapeVector, PerfFwdResultParams, vector_hash> cached_benchmark_fwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
+-  lru_unordered_map<TensorShapeVector, PerfBwdResultParams, vector_hash> cached_benchmark_bwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
+-
+   // Some properties needed to support asymmetric padded Conv nodes
+   bool post_slicing_required;
+   TensorShapeVector slice_starts;
+diff --git a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
+index 7447113fdf..a662e35b2e 100644
+--- a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
++++ b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
+@@ -76,7 +76,6 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
+
+       if (w_dims_changed) {
+         s_.last_w_dims = gsl::make_span(w_dims);
+-        s_.cached_benchmark_bwd_results.clear();
+       }
+
+       ConvTransposeAttributes::Prepare p;
+@@ -126,35 +125,29 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
+       }
+
+       y_data = reinterpret_cast<HipT*>(p.Y->MutableData<T>());
+-
+-      if (!s_.cached_benchmark_bwd_results.contains(x_dims)) {
+-        IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
+-
+-        miopenConvAlgoPerf_t perf;
+-        int algo_count = 1;
+-        MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionBackwardDataAlgorithm(
+-            GetMiopenHandle(context),
+-            s_.x_tensor,
+-            x_data,
+-            s_.w_desc,
+-            w_data,
+-            s_.conv_desc,
+-            s_.y_tensor,
+-            y_data,
+-            1,
+-            &algo_count,
+-            &perf,
+-            algo_search_workspace.get(),
+-            AlgoSearchWorkspaceSize,
+-            false));
+-        s_.cached_benchmark_bwd_results.insert(x_dims, {perf.bwd_data_algo, perf.memory});
+-      }
+-
+-      const auto& perf = s_.cached_benchmark_bwd_results.at(x_dims);
+-      s_.bwd_data_algo = perf.bwd_data_algo;
+-      s_.workspace_bytes = perf.memory;
+     }
+
++    IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
++    miopenConvAlgoPerf_t perf;
++    int algo_count = 1;
++    MIOPEN_RETURN_IF_ERROR(miopenFindConvolutionBackwardDataAlgorithm(
++        GetMiopenHandle(context),
++        s_.x_tensor,
++        x_data,
++        s_.w_desc,
++        w_data,
++        s_.conv_desc,
++        s_.y_tensor,
++        y_data,
++        1,
++        &algo_count,
++        &perf,
++        algo_search_workspace.get(),
++        AlgoSearchWorkspaceSize,
++        false));
++    s_.bwd_data_algo = perf.bwd_data_algo;
++    s_.workspace_bytes = perf.memory;
++
+     // The following block will be executed in case there has been no change in the shapes of the
+     // input and the filter compared to the previous run
+     if (!y_data) {

machine-learning/patches/0002-target-gfx900-gfx1102.patch

@@ -0,0 +1,13 @@
+diff --git a/cmake/CMakeLists.txt b/cmake/CMakeLists.txt
+index d90a2a355..bb1a7de12 100644
+--- a/cmake/CMakeLists.txt
++++ b/cmake/CMakeLists.txt
+@@ -295,7 +295,7 @@ if (onnxruntime_USE_ROCM)
+   endif()
+
+   if (NOT CMAKE_HIP_ARCHITECTURES)
+-    set(CMAKE_HIP_ARCHITECTURES "gfx908;gfx90a;gfx1030;gfx1100;gfx1101;gfx940;gfx941;gfx942;gfx1200;gfx1201")
++    set(CMAKE_HIP_ARCHITECTURES "gfx900;gfx908;gfx90a;gfx1030;gfx1100;gfx1101;gfx1102;gfx940;gfx941;gfx942;gfx1200;gfx1201")
+   endif()
+
+   file(GLOB rocm_cmake_components ${onnxruntime_ROCM_HOME}/lib/cmake/*)

machine-learning/pyproject.toml

@@ -51,6 +51,8 @@ cpu = ["onnxruntime>=1.15.0,<2"]
 cuda = ["onnxruntime-gpu>=1.17.0,<2"]
 openvino = ["onnxruntime-openvino>=1.17.1,<1.19.0"]
 armnn = ["onnxruntime>=1.15.0,<2"]
+rknn = ["onnxruntime>=1.15.0,<2", "rknn-toolkit-lite2>=2.3.0,<3"]
+rocm = []
 
 [tool.uv]
 compile-bytecode = true

machine-learning/start.sh

@@ -2,16 +2,19 @@
 
 echo "Initializing Immich ML $IMMICH_SOURCE_REF"
 
-lib_path="/usr/lib/$(arch)-linux-gnu/libmimalloc.so.2"
-# mimalloc seems to increase memory usage dramatically with openvino, need to investigate
 if ! [ "$DEVICE" = "openvino" ]; then
-	export LD_PRELOAD="$lib_path"
-	export LD_BIND_NOW=1
 	: "${MACHINE_LEARNING_WORKER_TIMEOUT:=120}"
 else
 	: "${MACHINE_LEARNING_WORKER_TIMEOUT:=300}"
 fi
 
+# mimalloc seems to increase memory usage dramatically with openvino, need to investigate
+if ! [ "$DEVICE" = "openvino" ] && ! [ "$DEVICE" = "rocm" ]; then
+	lib_path="/usr/lib/$(arch)-linux-gnu/libmimalloc.so.2"
+	export LD_PRELOAD="$lib_path"
+	export LD_BIND_NOW=1
+fi
+
 : "${IMMICH_HOST:=[::]}"
 : "${IMMICH_PORT:=3003}"
 : "${MACHINE_LEARNING_WORKERS:=1}"

machine-learning/uv.lock

@@ -1109,6 +1109,10 @@ cuda = [
 openvino = [
     { name = "onnxruntime-openvino" },
 ]
+rknn = [
+    { name = "onnxruntime" },
+    { name = "rknn-toolkit-lite2" },
+]
 
 [package.dev-dependencies]
 dev = [
@@ -1162,6 +1166,7 @@ requires-dist = [
     { name = "insightface", specifier = ">=0.7.3,<1.0" },
     { name = "onnxruntime", marker = "extra == 'armnn'", specifier = ">=1.15.0,<2" },
     { name = "onnxruntime", marker = "extra == 'cpu'", specifier = ">=1.15.0,<2" },
+    { name = "onnxruntime", marker = "extra == 'rknn'", specifier = ">=1.15.0,<2" },
     { name = "onnxruntime-gpu", marker = "extra == 'cuda'", specifier = ">=1.17.0,<2", index = "https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-cuda-12/pypi/simple/" },
     { name = "onnxruntime-openvino", marker = "extra == 'openvino'", specifier = ">=1.17.1,<1.19.0" },
     { name = "opencv-python-headless", specifier = ">=4.7.0.72,<5.0" },
@@ -1171,10 +1176,11 @@ requires-dist = [
     { name = "pydantic-settings", specifier = ">=2.5.2,<3" },
     { name = "python-multipart", specifier = ">=0.0.6,<1.0" },
     { name = "rich", specifier = ">=13.4.2" },
+    { name = "rknn-toolkit-lite2", marker = "extra == 'rknn'", specifier = ">=2.3.0,<3" },
     { name = "tokenizers", specifier = ">=0.15.0,<1.0" },
     { name = "uvicorn", extras = ["standard"], specifier = ">=0.22.0,<1.0" },
 ]
-provides-extras = ["cpu", "cuda", "openvino", "armnn"]
+provides-extras = ["cpu", "cuda", "openvino", "armnn", "rknn", "rocm"]
 
 [package.metadata.requires-dev]
 dev = [
@@ -2131,6 +2137,77 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/19/71/39c7c0d87f8d4e6c020a393182060eaefeeae6c01dab6a84ec346f2567df/rich-13.9.4-py3-none-any.whl", hash = "sha256:6049d5e6ec054bf2779ab3358186963bac2ea89175919d699e378b99738c2a90", size = 242424 },
 ]
 
+[[package]]
+name = "rknn-toolkit-lite2"
+version = "2.3.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+    { name = "psutil" },
+    { name = "ruamel-yaml" },
+]
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/ed/77/6af374a4a8cd2aee762a1fb8a3050dcf3f129134bbdc4bb6bed755c4325b/rknn_toolkit_lite2-2.3.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4b6733689bd09a262bcb6ba4744e690dd4b37ebeac4ed427cf45242c4b4ce9a4", size = 559372 },
+    { url = "https://files.pythonhosted.org/packages/9b/0c/76ff1eb09d09ce4394a6959d2343a321d28dd9e604348ffdafceafdc344c/rknn_toolkit_lite2-2.3.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e3e4fefe355dc34a155680e4bcb9e4abb37ebc271f045ec9e0a4a3a018bc5beb", size = 569149 },
+    { url = "https://files.pythonhosted.org/packages/0d/6e/8679562028051b02312212defc6e8c07248953f10dd7ad506e941b575bf3/rknn_toolkit_lite2-2.3.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:37394371d1561f470c553f39869d7c35ff93405dffe3d0d72babf297a2b0aee9", size = 527457 },
+]
+
+[[package]]
+name = "ruamel-yaml"
+version = "0.18.10"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "ruamel-yaml-clib", marker = "python_full_version < '3.13' and platform_python_implementation == 'CPython'" },
+]
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+]
+
 [[package]]
 name = "ruff"
 version = "0.9.9"

mobile/assets/i18n/en-US.json

@@ -197,7 +197,7 @@
   "control_bottom_app_bar_edit_time": "Edit Date & Time",
   "control_bottom_app_bar_favorite": "Favorite",
   "control_bottom_app_bar_share": "Share",
-  "control_bottom_app_bar_share_to": "Share To",
+  "control_bottom_app_bar_share_link": "Share Link",
   "control_bottom_app_bar_stack": "Stack",
   "control_bottom_app_bar_trash_from_immich": "Move to Trash",
   "control_bottom_app_bar_unarchive": "Unarchive",
@@ -264,7 +264,9 @@
   "exif_bottom_sheet_location_add": "Add a location",
   "exif_bottom_sheet_people": "PEOPLE",
   "exif_bottom_sheet_person_add_person": "Add name",
-  "exif_bottom_sheet_person_age": "Age {}",
+  "exif_bottom_sheet_person_age_years": "Age {}",
+  "exif_bottom_sheet_person_age_year_months": "Age 1 year, {} months",
+  "exif_bottom_sheet_person_age_months": "Age {} months",
   "experimental_settings_new_asset_list_subtitle": "Work in progress",
   "experimental_settings_new_asset_list_title": "Enable experimental photo grid",
   "experimental_settings_subtitle": "Use at your own risk!",

mobile/lib/domain/interfaces/user.interface.dart

@@ -4,8 +4,6 @@ import 'package:immich_mobile/domain/models/user.model.dart';
 abstract interface class IUserRepository implements IDatabaseRepository {
   Future<bool> insert(UserDto user);
 
-  Future<UserDto?> get(int id);
-
   Future<UserDto?> getByUserId(String id);
 
   Future<List<UserDto?>> getByUserIds(List<String> ids);
@@ -16,7 +14,7 @@ abstract interface class IUserRepository implements IDatabaseRepository {
 
   Future<UserDto> update(UserDto user);
 
-  Future<void> delete(List<int> ids);
+  Future<void> delete(List<String> ids);
 
   Future<void> deleteAll();
 }

mobile/lib/domain/models/user.model.dart

@@ -1,7 +1,5 @@
 import 'dart:ui';
 
-import 'package:immich_mobile/utils/hash.dart';
-
 enum AvatarColor {
   // do not change this order or reuse indices for other purposes, adding is OK
   primary,
@@ -32,7 +30,7 @@ enum AvatarColor {
 
 // TODO: Rename to User once Isar is removed
 class UserDto {
-  final String uid;
+  final String id;
   final String email;
   final String name;
   final bool isAdmin;
@@ -50,11 +48,10 @@ class UserDto {
   final int quotaUsageInBytes;
   final int quotaSizeInBytes;
 
-  int get id => fastHash(uid);
   bool get hasQuota => quotaSizeInBytes > 0;
 
   const UserDto({
-    required this.uid,
+    required this.id,
     required this.email,
     required this.name,
     required this.isAdmin,
@@ -73,7 +70,6 @@ class UserDto {
   String toString() {
     return '''User: {
 id: $id,
-uid: $uid,
 email: $email,
 name: $name,
 isAdmin: $isAdmin,
@@ -90,7 +86,7 @@ quotaSizeInBytes: $quotaSizeInBytes,
   }
 
   UserDto copyWith({
-    String? uid,
+    String? id,
     String? email,
     String? name,
     bool? isAdmin,
@@ -105,7 +101,7 @@ quotaSizeInBytes: $quotaSizeInBytes,
     int? quotaSizeInBytes,
   }) =>
       UserDto(
-        uid: uid ?? this.uid,
+        id: id ?? this.id,
         email: email ?? this.email,
         name: name ?? this.name,
         isAdmin: isAdmin ?? this.isAdmin,
@@ -124,7 +120,7 @@ quotaSizeInBytes: $quotaSizeInBytes,
   bool operator ==(covariant UserDto other) {
     if (identical(this, other)) return true;
 
-    return other.uid == uid &&
+    return other.id == id &&
         other.updatedAt.isAtSameMomentAs(updatedAt) &&
         other.avatarColor == avatarColor &&
         other.email == email &&
@@ -141,7 +137,7 @@ quotaSizeInBytes: $quotaSizeInBytes,
 
   @override
   int get hashCode =>
-      uid.hashCode ^
+      id.hashCode ^
       name.hashCode ^
       email.hashCode ^
       updatedAt.hashCode ^

mobile/lib/domain/services/user.service.dart

@@ -44,10 +44,14 @@ class UserService {
 
   Future<String?> createProfileImage(String name, Uint8List image) async {
     try {
-      return await _userApiRepository.createProfileImage(
+      final path = await _userApiRepository.createProfileImage(
         name: name,
         data: image,
       );
+      final updatedUser = getMyUser().copyWith(profileImagePath: path);
+      await _storeService.put(StoreKey.currentUser, updatedUser);
+      await _userRepository.update(updatedUser);
+      return path;
     } catch (e) {
       _log.warning("Failed to upload profile image", e);
       return null;

mobile/lib/extensions/collection_extensions.dart

@@ -3,6 +3,7 @@ import 'dart:typed_data';
 import 'package:collection/collection.dart';
 import 'package:immich_mobile/domain/models/user.model.dart';
 import 'package:immich_mobile/entities/asset.entity.dart';
+import 'package:immich_mobile/utils/hash.dart';
 
 extension ListExtension<E> on List<E> {
   List<E> uniqueConsecutive({
@@ -62,11 +63,11 @@ extension AssetListExtension on Iterable<Asset> {
     void Function()? errorCallback,
   }) {
     if (owner == null) return [];
-    final userId = owner.id;
+    final isarUserId = fastHash(owner.id);
-    final bool onlyOwned = every((e) => e.ownerId == userId);
+    final bool onlyOwned = every((e) => e.ownerId == isarUserId);
     if (!onlyOwned) {
       if (errorCallback != null) errorCallback();
-      return where((a) => a.ownerId == userId);
+      return where((a) => a.ownerId == isarUserId);
     }
     return this;
   }

mobile/lib/infrastructure/entities/user.entity.dart

@@ -40,7 +40,7 @@ class User {
   });
 
   static User fromDto(UserDto dto) => User(
-        id: dto.uid,
+        id: dto.id,
         updatedAt: dto.updatedAt,
         email: dto.email,
         name: dto.name,
@@ -56,7 +56,7 @@ class User {
       );
 
   UserDto toDto() => UserDto(
-        uid: id,
+        id: id,
         email: email,
         name: name,
         isAdmin: isAdmin,

mobile/lib/infrastructure/repositories/store.repository.dart

@@ -78,7 +78,9 @@ class IsarStoreRepository extends IsarDatabaseRepository
         const (DateTime) => entity.intValue == null
             ? null
             : DateTime.fromMillisecondsSinceEpoch(entity.intValue!),
-        const (UserDto) => await IsarUserRepository(_db).get(entity.intValue!),
+        const (UserDto) => entity.strValue == null
+            ? null
+            : await IsarUserRepository(_db).getByUserId(entity.strValue!),
         _ => null,
       } as T?;
 
@@ -89,8 +91,8 @@ class IsarStoreRepository extends IsarDatabaseRepository
       const (bool) => ((value as bool) ? 1 : 0, null),
       const (DateTime) => ((value as DateTime).millisecondsSinceEpoch, null),
       const (UserDto) => (
-          (await IsarUserRepository(_db).update(value as UserDto)).id,
           null,
+          (await IsarUserRepository(_db).update(value as UserDto)).id,
         ),
       _ => throw UnsupportedError(
           "Unsupported primitive type: ${key.type} for key: ${key.name}",

mobile/lib/infrastructure/repositories/user.repository.dart

@@ -11,9 +11,9 @@ class IsarUserRepository extends IsarDatabaseRepository
   const IsarUserRepository(super.db) : _db = db;
 
   @override
-  Future<void> delete(List<int> ids) async {
+  Future<void> delete(List<String> ids) async {
     await transaction(() async {
-      await _db.users.deleteAll(ids);
+      await _db.users.deleteAllById(ids);
     });
   }
 
@@ -24,11 +24,6 @@ class IsarUserRepository extends IsarDatabaseRepository
     });
   }
 
-  @override
-  Future<UserDto?> get(int id) async {
-    return (await _db.users.get(id))?.toDto();
-  }
-
   @override
   Future<List<UserDto>> getAll({SortUserBy? sortBy}) async {
     return (await _db.users

mobile/lib/infrastructure/utils/user.converter.dart

@@ -4,7 +4,7 @@ import 'package:openapi/api.dart';
 abstract final class UserConverter {
   /// Base user dto used where the complete user object is not required
   static UserDto fromSimpleUserDto(UserResponseDto dto) => UserDto(
-        uid: dto.id,
+        id: dto.id,
         email: dto.email,
         name: dto.name,
         isAdmin: false,
@@ -18,7 +18,7 @@ abstract final class UserConverter {
     UserPreferencesResponseDto? preferenceDto,
   ]) =>
       UserDto(
-        uid: adminDto.id,
+        id: adminDto.id,
         email: adminDto.email,
         name: adminDto.name,
         isAdmin: adminDto.isAdmin,
@@ -34,7 +34,7 @@ abstract final class UserConverter {
       );
 
   static UserDto fromPartnerDto(PartnerResponseDto dto) => UserDto(
-        uid: dto.id,
+        id: dto.id,
         email: dto.email,
         name: dto.name,
         isAdmin: false,

mobile/lib/interfaces/asset.interface.dart

@@ -19,7 +19,7 @@ abstract interface class IAssetRepository implements IDatabaseRepository {
   );
 
   Future<List<Asset>> getAll({
-    required int ownerId,
+    required String ownerId,
     AssetState? state,
     AssetSort? sortBy,
     int? limit,
@@ -29,8 +29,8 @@ abstract interface class IAssetRepository implements IDatabaseRepository {
 
   Future<List<Asset>> getByAlbum(
     Album album, {
-    Iterable<int> notOwnedBy = const [],
+    Iterable<String> notOwnedBy = const [],
-    int? ownerId,
+    String? ownerId,
     AssetState? state,
     AssetSort? sortBy,
   });
@@ -45,7 +45,7 @@ abstract interface class IAssetRepository implements IDatabaseRepository {
 
   Future<List<Asset>> getMatches({
     required List<Asset> assets,
-    required int ownerId,
+    required String ownerId,
     AssetState? state,
     int limit = 100,
   });
@@ -64,10 +64,10 @@ abstract interface class IAssetRepository implements IDatabaseRepository {
 
   Stream<Asset?> watchAsset(int id, {bool fireImmediately = false});
 
-  Future<List<Asset>> getTrashAssets(int userId);
+  Future<List<Asset>> getTrashAssets(String userId);
 
-  Future<List<Asset>> getRecentlyAddedAssets(int userId);
+  Future<List<Asset>> getRecentlyAddedAssets(String userId);
-  Future<List<Asset>> getMotionAssets(int userId);
+  Future<List<Asset>> getMotionAssets(String userId);
 }
 
 enum AssetSort { checksum, ownerIdChecksum }

mobile/lib/interfaces/etag.interface.dart

@@ -2,7 +2,7 @@ import 'package:immich_mobile/entities/etag.entity.dart';
 import 'package:immich_mobile/interfaces/database.interface.dart';
 
 abstract interface class IETagRepository implements IDatabaseRepository {
-  Future<ETag?> get(int id);
+  Future<ETag?> get(String id);
 
   Future<ETag?> getById(String id);
 

mobile/lib/interfaces/timeline.interface.dart

@@ -3,22 +3,25 @@ import 'package:immich_mobile/entities/asset.entity.dart';
 import 'package:immich_mobile/widgets/asset_grid/asset_grid_data_structure.dart';
 
 abstract class ITimelineRepository {
-  Future<List<int>> getTimelineUserIds(int id);
+  Future<List<String>> getTimelineUserIds(String id);
 
-  Stream<List<int>> watchTimelineUsers(int id);
+  Stream<List<String>> watchTimelineUsers(String id);
 
-  Stream<RenderList> watchArchiveTimeline(int userId);
+  Stream<RenderList> watchArchiveTimeline(String userId);
-  Stream<RenderList> watchFavoriteTimeline(int userId);
+  Stream<RenderList> watchFavoriteTimeline(String userId);
-  Stream<RenderList> watchTrashTimeline(int userId);
+  Stream<RenderList> watchTrashTimeline(String userId);
   Stream<RenderList> watchAlbumTimeline(
     Album album,
     GroupAssetsBy groupAssetsBy,
   );
   Stream<RenderList> watchAllVideosTimeline();
 
-  Stream<RenderList> watchHomeTimeline(int userId, GroupAssetsBy groupAssetsBy);
+  Stream<RenderList> watchHomeTimeline(
+    String userId,
+    GroupAssetsBy groupAssetsBy,
+  );
   Stream<RenderList> watchMultiUsersTimeline(
-    List<int> userIds,
+    List<String> userIds,
     GroupAssetsBy groupAssetsBy,
   );
 
@@ -27,5 +30,5 @@ abstract class ITimelineRepository {
     GroupAssetsBy getGroupByOption,
   );
 
-  Stream<RenderList> watchAssetSelectionTimeline(int userId);
+  Stream<RenderList> watchAssetSelectionTimeline(String userId);
 }

mobile/lib/pages/album/album_additional_shared_user_selection.page.dart

@@ -26,7 +26,7 @@ class AlbumAdditionalSharedUserSelectionPage extends HookConsumerWidget {
     final sharedUsersList = useState<Set<UserDto>>({});
 
     addNewUsersHandler() {
-      context.maybePop(sharedUsersList.value.map((e) => e.uid).toList());
+      context.maybePop(sharedUsersList.value.map((e) => e.id).toList());
     }
 
     buildTileIcon(UserDto user) {
@@ -151,7 +151,7 @@ class AlbumAdditionalSharedUserSelectionPage extends HookConsumerWidget {
         onData: (users) {
           for (var sharedUsers in album.sharedUsers) {
             users.removeWhere(
-              (u) => u.uid == sharedUsers.id || u.uid == album.ownerId,
+              (u) => u.id == sharedUsers.id || u.id == album.ownerId,
             );
           }
 

mobile/lib/pages/album/album_options.page.dart

@@ -85,7 +85,7 @@ class AlbumOptionsPage extends HookConsumerWidget {
     void handleUserClick(UserDto user) {
       var actions = [];
 
-      if (user.uid == userId) {
+      if (user.id == userId) {
         actions = [
           ListTile(
             leading: const Icon(Icons.exit_to_app_rounded),
@@ -170,10 +170,10 @@ class AlbumOptionsPage extends HookConsumerWidget {
                 color: context.colorScheme.onSurfaceSecondary,
               ),
             ),
-            trailing: userId == user.uid || isOwner
+            trailing: userId == user.id || isOwner
                 ? const Icon(Icons.more_horiz_rounded)
                 : const SizedBox(),
-            onTap: userId == user.uid || isOwner
+            onTap: userId == user.id || isOwner
                 ? () => handleUserClick(user)
                 : null,
           );

mobile/lib/pages/albums/albums.page.dart

@@ -33,7 +33,7 @@ class AlbumsPage extends HookConsumerWidget {
     final searchController = useTextEditingController();
     final debounceTimer = useRef<Timer?>(null);
     final filterMode = useState(QuickFilterMode.all);
-    final userId = ref.watch(currentUserProvider)?.uid;
+    final userId = ref.watch(currentUserProvider)?.id;
     final searchFocusNode = useFocusNode();
 
     toggleViewMode() {

mobile/lib/pages/common/activities.page.dart

@@ -72,7 +72,7 @@ class ActivitiesPage extends HookConsumerWidget {
 
                     final activity = data[index];
                     final canDelete = activity.user.id == user?.id ||
-                        album.ownerId == user?.uid;
+                        album.ownerId == user?.id;
 
                     return Padding(
                       padding: const EdgeInsets.all(5),

mobile/lib/providers/auth.provider.dart

@@ -3,11 +3,12 @@ import 'package:flutter_udid/flutter_udid.dart';
 import 'package:hooks_riverpod/hooks_riverpod.dart';
 import 'package:immich_mobile/domain/models/store.model.dart';
 import 'package:immich_mobile/domain/models/user.model.dart';
+import 'package:immich_mobile/domain/services/user.service.dart';
 import 'package:immich_mobile/entities/store.entity.dart';
-import 'package:immich_mobile/infrastructure/utils/user.converter.dart';
 import 'package:immich_mobile/models/auth/auth_state.model.dart';
 import 'package:immich_mobile/models/auth/login_response.model.dart';
 import 'package:immich_mobile/providers/api.provider.dart';
+import 'package:immich_mobile/providers/infrastructure/user.provider.dart';
 import 'package:immich_mobile/services/api.service.dart';
 import 'package:immich_mobile/services/auth.service.dart';
 import 'package:immich_mobile/utils/hash.dart';
@@ -18,20 +19,20 @@ final authProvider = StateNotifierProvider<AuthNotifier, AuthState>((ref) {
   return AuthNotifier(
     ref.watch(authServiceProvider),
     ref.watch(apiServiceProvider),
+    ref.watch(userServiceProvider),
   );
 });
 
 class AuthNotifier extends StateNotifier<AuthState> {
   final AuthService _authService;
   final ApiService _apiService;
+  final UserService _userService;
   final _log = Logger("AuthenticationNotifier");
 
   static const Duration _timeoutDuration = Duration(seconds: 7);
 
-  AuthNotifier(
+  AuthNotifier(this._authService, this._apiService, this._userService)
-    this._authService,
+      : super(
-    this._apiService,
-  ) : super(
           AuthState(
             deviceId: "",
             userId: "",
@@ -106,17 +107,21 @@ class AuthNotifier extends StateNotifier<AuthState> {
     String deviceId =
         Store.tryGet(StoreKey.deviceId) ?? await FlutterUdid.consistentUdid;
 
-    UserDto? user = Store.tryGet(StoreKey.currentUser);
+    UserDto? user = _userService.tryGetMyUser();
 
-    UserAdminResponseDto? userResponse;
-    UserPreferencesResponseDto? userPreferences;
     try {
-      final responses = await Future.wait([
+      final serverUser =
-        _apiService.usersApi.getMyUser().timeout(_timeoutDuration),
+          await _userService.refreshMyUser().timeout(_timeoutDuration);
-        _apiService.usersApi.getMyPreferences().timeout(_timeoutDuration),
+      if (serverUser == null) {
-      ]);
+        _log.severe("Unable to get user information from the server.");
-      userResponse = responses[0] as UserAdminResponseDto;
+      } else {
-      userPreferences = responses[1] as UserPreferencesResponseDto;
+        // If the user information is successfully retrieved, update the store
+        // Due to the flow of the code, this will always happen on first login
+        user = serverUser;
+        await Store.put(StoreKey.deviceId, deviceId);
+        await Store.put(StoreKey.deviceIdHash, fastHash(deviceId));
+        await Store.put(StoreKey.accessToken, accessToken);
+      }
     } on ApiException catch (error, stackTrace) {
       if (error.code == 401) {
         _log.severe("Unauthorized access, token likely expired. Logging out.");
@@ -140,22 +145,6 @@ class AuthNotifier extends StateNotifier<AuthState> {
       }
     }
 
-    // If the user information is successfully retrieved, update the store
-    // Due to the flow of the code, this will always happen on first login
-    if (userResponse == null) {
-      _log.severe("Unable to get user information from the server.");
-    } else {
-      await Store.put(StoreKey.deviceId, deviceId);
-      await Store.put(StoreKey.deviceIdHash, fastHash(deviceId));
-      await Store.put(
-        StoreKey.currentUser,
-        UserConverter.fromAdminDto(userResponse, userPreferences),
-      );
-      await Store.put(StoreKey.accessToken, accessToken);
-
-      user = UserConverter.fromAdminDto(userResponse, userPreferences);
-    }
-
     // If the user is null, the login was not successful
     // and we don't have a local copy of the user from a prior successful login
     if (user == null) {
@@ -163,13 +152,13 @@ class AuthNotifier extends StateNotifier<AuthState> {
     }
 
     state = state.copyWith(
-      isAuthenticated: true,
-      userId: user.uid,
-      userEmail: user.email,
-      name: user.name,
-      profileImagePath: user.profileImagePath,
-      isAdmin: user.isAdmin,
       deviceId: deviceId,
+      userId: user.id,
+      userEmail: user.email,
+      isAuthenticated: true,
+      name: user.name,
+      isAdmin: user.isAdmin,
+      profileImagePath: user.profileImagePath,
     );
 
     return true;

mobile/lib/providers/timeline.provider.dart

@@ -5,7 +5,7 @@ import 'package:immich_mobile/providers/locale_provider.dart';
 import 'package:immich_mobile/services/timeline.service.dart';
 import 'package:immich_mobile/widgets/asset_grid/asset_grid_data_structure.dart';
 
-final singleUserTimelineProvider = StreamProvider.family<RenderList, int?>(
+final singleUserTimelineProvider = StreamProvider.family<RenderList, String?>(
   (ref, userId) {
     if (userId == null) {
       return const Stream.empty();
@@ -18,7 +18,8 @@ final singleUserTimelineProvider = StreamProvider.family<RenderList, int?>(
   dependencies: [localeProvider],
 );
 
-final multiUsersTimelineProvider = StreamProvider.family<RenderList, List<int>>(
+final multiUsersTimelineProvider =
+    StreamProvider.family<RenderList, List<String>>(
   (ref, userIds) {
     ref.watch(localeProvider);
     final timelineService = ref.watch(timelineServiceProvider);

mobile/lib/providers/user.provider.dart

@@ -1,34 +1,24 @@
 import 'dart:async';
 
 import 'package:hooks_riverpod/hooks_riverpod.dart';
-import 'package:immich_mobile/domain/models/store.model.dart';
 import 'package:immich_mobile/domain/models/user.model.dart';
-import 'package:immich_mobile/entities/store.entity.dart';
+import 'package:immich_mobile/domain/services/user.service.dart';
-import 'package:immich_mobile/infrastructure/utils/user.converter.dart';
+import 'package:immich_mobile/providers/infrastructure/user.provider.dart';
-import 'package:immich_mobile/providers/api.provider.dart';
-import 'package:immich_mobile/services/api.service.dart';
 import 'package:immich_mobile/services/timeline.service.dart';
 
 class CurrentUserProvider extends StateNotifier<UserDto?> {
-  CurrentUserProvider(this._apiService) : super(null) {
+  CurrentUserProvider(this._userService) : super(null) {
-    state = Store.tryGet(StoreKey.currentUser);
+    state = _userService.tryGetMyUser();
     streamSub =
-        Store.watch(StoreKey.currentUser).listen((user) => state = user);
+        _userService.watchMyUser().listen((user) => state = user ?? state);
   }
 
-  final ApiService _apiService;
+  final UserService _userService;
   late final StreamSubscription<UserDto?> streamSub;
 
   refresh() async {
     try {
-      final user = await _apiService.usersApi.getMyUser();
+      await _userService.refreshMyUser();
-      final userPreferences = await _apiService.usersApi.getMyPreferences();
-      if (user != null) {
-        await Store.put(
-          StoreKey.currentUser,
-          UserConverter.fromAdminDto(user, userPreferences),
-        );
-      }
     } catch (_) {}
   }
 
@@ -41,12 +31,10 @@ class CurrentUserProvider extends StateNotifier<UserDto?> {
 
 final currentUserProvider =
     StateNotifierProvider<CurrentUserProvider, UserDto?>((ref) {
-  return CurrentUserProvider(
+  return CurrentUserProvider(ref.watch(userServiceProvider));
-    ref.watch(apiServiceProvider),
-  );
 });
 
-class TimelineUserIdsProvider extends StateNotifier<List<int>> {
+class TimelineUserIdsProvider extends StateNotifier<List<String>> {
   TimelineUserIdsProvider(this._timelineService) : super([]) {
     _timelineService.getTimelineUserIds().then((users) => state = users);
     streamSub = _timelineService
@@ -54,7 +42,7 @@ class TimelineUserIdsProvider extends StateNotifier<List<int>> {
         .listen((users) => state = users);
   }
 
-  late final StreamSubscription<List<int>> streamSub;
+  late final StreamSubscription<List<String>> streamSub;
   final TimelineService _timelineService;
 
   @override
@@ -65,6 +53,6 @@ class TimelineUserIdsProvider extends StateNotifier<List<int>> {
 }
 
 final timelineUsersIdsProvider =
-    StateNotifierProvider<TimelineUserIdsProvider, List<int>>((ref) {
+    StateNotifierProvider<TimelineUserIdsProvider, List<String>>((ref) {
   return TimelineUserIdsProvider(ref.watch(timelineServiceProvider));
 });

mobile/lib/repositories/album.repository.dart

@@ -10,6 +10,7 @@ import 'package:immich_mobile/interfaces/album.interface.dart';
 import 'package:immich_mobile/models/albums/album_search.model.dart';
 import 'package:immich_mobile/providers/db.provider.dart';
 import 'package:immich_mobile/repositories/database.repository.dart';
+import 'package:immich_mobile/utils/hash.dart';
 import 'package:isar/isar.dart';
 
 final albumRepositoryProvider =
@@ -43,14 +44,11 @@ class AlbumRepository extends DatabaseRepository implements IAlbumRepository {
     if (shared != null) {
       query = query.sharedEqualTo(shared);
     }
+    final isarUserId = fastHash(Store.get(StoreKey.currentUser).id);
     if (owner == true) {
-      query = query.owner(
+      query = query.owner((q) => q.isarIdEqualTo(isarUserId));
-        (q) => q.isarIdEqualTo(Store.get(StoreKey.currentUser).id),
-      );
     } else if (owner == false) {
-      query = query.owner(
+      query = query.owner((q) => q.not().isarIdEqualTo(isarUserId));
-        (q) => q.not().isarIdEqualTo(Store.get(StoreKey.currentUser).id),
-      );
     }
     if (remote == true) {
       query = query.localIdIsNull();
@@ -140,16 +138,13 @@ class AlbumRepository extends DatabaseRepository implements IAlbumRepository {
         .filter()
         .nameContains(searchTerm, caseSensitive: false)
         .remoteIdIsNotNull();
+    final isarUserId = fastHash(Store.get(StoreKey.currentUser).id);
 
     switch (filterMode) {
       case QuickFilterMode.sharedWithMe:
-        query = query.owner(
+        query = query.owner((q) => q.not().isarIdEqualTo(isarUserId));
-          (q) => q.not().isarIdEqualTo(Store.get(StoreKey.currentUser).id),
-        );
       case QuickFilterMode.myAlbums:
-        query = query.owner(
+        query = query.owner((q) => q.isarIdEqualTo(isarUserId));
-          (q) => q.isarIdEqualTo(Store.get(StoreKey.currentUser).id),
-        );
       case QuickFilterMode.all:
         break;
     }

mobile/lib/repositories/asset.repository.dart

@@ -11,6 +11,7 @@ import 'package:immich_mobile/infrastructure/entities/exif.entity.dart';
 import 'package:immich_mobile/interfaces/asset.interface.dart';
 import 'package:immich_mobile/providers/db.provider.dart';
 import 'package:immich_mobile/repositories/database.repository.dart';
+import 'package:immich_mobile/utils/hash.dart';
 import 'package:isar/isar.dart';
 
 final assetRepositoryProvider =
@@ -22,20 +23,21 @@ class AssetRepository extends DatabaseRepository implements IAssetRepository {
   @override
   Future<List<Asset>> getByAlbum(
     Album album, {
-    Iterable<int> notOwnedBy = const [],
+    Iterable<String> notOwnedBy = const [],
-    int? ownerId,
+    String? ownerId,
     AssetState? state,
     AssetSort? sortBy,
   }) {
     var query = album.assets.filter();
+    final isarUserIds = notOwnedBy.map(fastHash).toList();
     if (notOwnedBy.length == 1) {
-      query = query.not().ownerIdEqualTo(notOwnedBy.first);
+      query = query.not().ownerIdEqualTo(isarUserIds.first);
     } else if (notOwnedBy.isNotEmpty) {
       query =
-          query.not().anyOf(notOwnedBy, (q, int id) => q.ownerIdEqualTo(id));
+          query.not().anyOf(isarUserIds, (q, int id) => q.ownerIdEqualTo(id));
     }
     if (ownerId != null) {
-      query = query.ownerIdEqualTo(ownerId);
+      query = query.ownerIdEqualTo(fastHash(ownerId));
     }
 
     if (state != null) {
@@ -87,27 +89,28 @@ class AssetRepository extends DatabaseRepository implements IAssetRepository {
 
   @override
   Future<List<Asset>> getAll({
-    required int ownerId,
+    required String ownerId,
     AssetState? state,
     AssetSort? sortBy,
     int? limit,
   }) {
     final baseQuery = db.assets.where();
+    final isarUserIds = fastHash(ownerId);
     final QueryBuilder<Asset, Asset, QAfterFilterCondition> filteredQuery =
         switch (state) {
-      null => baseQuery.ownerIdEqualToAnyChecksum(ownerId).noOp(),
+      null => baseQuery.ownerIdEqualToAnyChecksum(isarUserIds).noOp(),
       AssetState.local => baseQuery
           .remoteIdIsNull()
           .filter()
           .localIdIsNotNull()
-          .ownerIdEqualTo(ownerId),
+          .ownerIdEqualTo(isarUserIds),
       AssetState.remote => baseQuery
           .localIdIsNull()
           .filter()
           .remoteIdIsNotNull()
-          .ownerIdEqualTo(ownerId),
+          .ownerIdEqualTo(isarUserIds),
       AssetState.merged => baseQuery
-          .ownerIdEqualToAnyChecksum(ownerId)
+          .ownerIdEqualToAnyChecksum(isarUserIds)
           .filter()
           .remoteIdIsNotNull()
           .localIdIsNotNull(),
@@ -132,7 +135,7 @@ class AssetRepository extends DatabaseRepository implements IAssetRepository {
   @override
   Future<List<Asset>> getMatches({
     required List<Asset> assets,
-    required int ownerId,
+    required String ownerId,
     AssetState? state,
     int limit = 100,
   }) {
@@ -147,7 +150,7 @@ class AssetRepository extends DatabaseRepository implements IAssetRepository {
       AssetState.merged =>
         baseQuery.localIdIsNotNull().filter().remoteIdIsNotNull(),
     };
-    return _getMatchesImpl(query, ownerId, assets, limit);
+    return _getMatchesImpl(query, fastHash(ownerId), assets, limit);
   }
 
   @override
@@ -185,10 +188,10 @@ class AssetRepository extends DatabaseRepository implements IAssetRepository {
 
   @override
   Future<List<Asset?>> getAllByOwnerIdChecksum(
-    List<int> ids,
+    List<int> ownerIds,
     List<String> checksums,
   ) =>
-      db.assets.getAllByOwnerIdChecksum(ids, checksums);
+      db.assets.getAllByOwnerIdChecksum(ownerIds, checksums);
 
   @override
   Future<List<Asset>> getAllLocal() =>
@@ -224,30 +227,30 @@ class AssetRepository extends DatabaseRepository implements IAssetRepository {
   }
 
   @override
-  Future<List<Asset>> getTrashAssets(int userId) {
+  Future<List<Asset>> getTrashAssets(String userId) {
     return db.assets
         .where()
         .remoteIdIsNotNull()
         .filter()
-        .ownerIdEqualTo(userId)
+        .ownerIdEqualTo(fastHash(userId))
         .isTrashedEqualTo(true)
         .findAll();
   }
 
   @override
-  Future<List<Asset>> getRecentlyAddedAssets(int userId) {
+  Future<List<Asset>> getRecentlyAddedAssets(String userId) {
     return db.assets
         .where()
-        .ownerIdEqualToAnyChecksum(userId)
+        .ownerIdEqualToAnyChecksum(fastHash(userId))
         .sortByFileCreatedAtDesc()
         .findAll();
   }
 
   @override
-  Future<List<Asset>> getMotionAssets(int userId) {
+  Future<List<Asset>> getMotionAssets(String userId) {
     return db.assets
         .where()
-        .ownerIdEqualToAnyChecksum(userId)
+        .ownerIdEqualToAnyChecksum(fastHash(userId))
         .filter()
         .livePhotoVideoIdIsNotNull()
         .findAll();

mobile/lib/repositories/asset_media.repository.dart

@@ -4,6 +4,7 @@ import 'package:immich_mobile/domain/models/store.model.dart';
 import 'package:immich_mobile/entities/asset.entity.dart';
 import 'package:immich_mobile/entities/store.entity.dart';
 import 'package:immich_mobile/interfaces/asset_media.interface.dart';
+import 'package:immich_mobile/utils/hash.dart';
 import 'package:photo_manager/photo_manager.dart' hide AssetType;
 
 final assetMediaRepositoryProvider = Provider((ref) => AssetMediaRepository());
@@ -24,7 +25,7 @@ class AssetMediaRepository implements IAssetMediaRepository {
     final Asset asset = Asset(
       checksum: "",
       localId: local.id,
-      ownerId: Store.get(StoreKey.currentUser).id,
+      ownerId: fastHash(Store.get(StoreKey.currentUser).id),
       fileCreatedAt: local.createDateTime,
       fileModifiedAt: local.modifiedDateTime,
       updatedAt: local.modifiedDateTime,

mobile/lib/repositories/etag.repository.dart

@@ -15,7 +15,7 @@ class ETagRepository extends DatabaseRepository implements IETagRepository {
   Future<List<String>> getAllIds() => db.eTags.where().idProperty().findAll();
 
   @override
-  Future<ETag?> get(int id) => db.eTags.get(id);
+  Future<ETag?> get(String id) => db.eTags.getById(id);
 
   @override
   Future<void> upsertAll(List<ETag> etags) => txn(() => db.eTags.putAll(etags));

mobile/lib/repositories/timeline.repository.dart

@@ -6,6 +6,7 @@ import 'package:immich_mobile/infrastructure/entities/user.entity.dart';
 import 'package:immich_mobile/interfaces/timeline.interface.dart';
 import 'package:immich_mobile/providers/db.provider.dart';
 import 'package:immich_mobile/repositories/database.repository.dart';
+import 'package:immich_mobile/utils/hash.dart';
 import 'package:immich_mobile/widgets/asset_grid/asset_grid_data_structure.dart';
 import 'package:isar/isar.dart';
 
@@ -17,32 +18,32 @@ class TimelineRepository extends DatabaseRepository
   TimelineRepository(super.db);
 
   @override
-  Future<List<int>> getTimelineUserIds(int id) {
+  Future<List<String>> getTimelineUserIds(String id) {
     return db.users
         .filter()
         .inTimelineEqualTo(true)
         .or()
-        .isarIdEqualTo(id)
+        .idEqualTo(id)
-        .isarIdProperty()
+        .idProperty()
         .findAll();
   }
 
   @override
-  Stream<List<int>> watchTimelineUsers(int id) {
+  Stream<List<String>> watchTimelineUsers(String id) {
     return db.users
         .filter()
         .inTimelineEqualTo(true)
         .or()
-        .isarIdEqualTo(id)
+        .idEqualTo(id)
-        .isarIdProperty()
+        .idProperty()
         .watch();
   }
 
   @override
-  Stream<RenderList> watchArchiveTimeline(int userId) {
+  Stream<RenderList> watchArchiveTimeline(String userId) {
     final query = db.assets
         .where()
-        .ownerIdEqualToAnyChecksum(userId)
+        .ownerIdEqualToAnyChecksum(fastHash(userId))
         .filter()
         .isArchivedEqualTo(true)
         .isTrashedEqualTo(false)
@@ -52,10 +53,10 @@ class TimelineRepository extends DatabaseRepository
   }
 
   @override
-  Stream<RenderList> watchFavoriteTimeline(int userId) {
+  Stream<RenderList> watchFavoriteTimeline(String userId) {
     final query = db.assets
         .where()
-        .ownerIdEqualToAnyChecksum(userId)
+        .ownerIdEqualToAnyChecksum(fastHash(userId))
         .filter()
         .isFavoriteEqualTo(true)
         .isTrashedEqualTo(false)
@@ -79,10 +80,10 @@ class TimelineRepository extends DatabaseRepository
   }
 
   @override
-  Stream<RenderList> watchTrashTimeline(int userId) {
+  Stream<RenderList> watchTrashTimeline(String userId) {
     final query = db.assets
         .filter()
-        .ownerIdEqualTo(userId)
+        .ownerIdEqualTo(fastHash(userId))
         .isTrashedEqualTo(true)
         .sortByFileCreatedAtDesc();
 
@@ -103,12 +104,12 @@ class TimelineRepository extends DatabaseRepository
 
   @override
   Stream<RenderList> watchHomeTimeline(
-    int userId,
+    String userId,
     GroupAssetsBy groupAssetByOption,
   ) {
     final query = db.assets
         .where()
-        .ownerIdEqualToAnyChecksum(userId)
+        .ownerIdEqualToAnyChecksum(fastHash(userId))
         .filter()
         .isArchivedEqualTo(false)
         .isTrashedEqualTo(false)
@@ -120,12 +121,13 @@ class TimelineRepository extends DatabaseRepository
 
   @override
   Stream<RenderList> watchMultiUsersTimeline(
-    List<int> userIds,
+    List<String> userIds,
     GroupAssetsBy groupAssetByOption,
   ) {
+    final isarUserIds = userIds.map(fastHash).toList();
     final query = db.assets
         .where()
-        .anyOf(userIds, (qb, userId) => qb.ownerIdEqualToAnyChecksum(userId))
+        .anyOf(isarUserIds, (qb, id) => qb.ownerIdEqualToAnyChecksum(id))
         .filter()
         .isArchivedEqualTo(false)
         .isTrashedEqualTo(false)
@@ -143,12 +145,12 @@ class TimelineRepository extends DatabaseRepository
   }
 
   @override
-  Stream<RenderList> watchAssetSelectionTimeline(int userId) {
+  Stream<RenderList> watchAssetSelectionTimeline(String userId) {
     final query = db.assets
         .where()
         .remoteIdIsNotNull()
         .filter()
-        .ownerIdEqualTo(userId)
+        .ownerIdEqualTo(fastHash(userId))
         .isTrashedEqualTo(false)
         .stackPrimaryAssetIdIsNull()
         .sortByFileCreatedAtDesc();

mobile/lib/routing/tab_navigation_observer.dart

@@ -1,11 +1,8 @@
 import 'package:auto_route/auto_route.dart';
 import 'package:flutter/foundation.dart';
 import 'package:hooks_riverpod/hooks_riverpod.dart';
-import 'package:immich_mobile/domain/models/store.model.dart';
-import 'package:immich_mobile/entities/store.entity.dart';
-import 'package:immich_mobile/infrastructure/utils/user.converter.dart';
-import 'package:immich_mobile/providers/api.provider.dart';
 import 'package:immich_mobile/providers/asset.provider.dart';
+import 'package:immich_mobile/providers/infrastructure/user.provider.dart';
 import 'package:immich_mobile/providers/memory.provider.dart';
 import 'package:immich_mobile/providers/server_info.provider.dart';
 
@@ -28,19 +25,7 @@ class TabNavigationObserver extends AutoRouterObserver {
 
       // Update user info
       try {
-        final userResponseDto =
+        ref.read(userServiceProvider).refreshMyUser();
-            await ref.read(apiServiceProvider).usersApi.getMyUser();
-        final userPreferences =
-            await ref.read(apiServiceProvider).usersApi.getMyPreferences();
-
-        if (userResponseDto == null) {
-          return;
-        }
-
-        await Store.put(
-          StoreKey.currentUser,
-          UserConverter.fromAdminDto(userResponseDto, userPreferences),
-        );
         ref.read(serverInfoProvider.notifier).getServerVersion();
       } catch (e) {
         debugPrint("Error refreshing user info $e");

mobile/lib/services/album.service.dart

@@ -6,12 +6,11 @@ import 'package:collection/collection.dart';
 import 'package:flutter/foundation.dart';
 import 'package:hooks_riverpod/hooks_riverpod.dart';
 import 'package:immich_mobile/constants/enums.dart';
-import 'package:immich_mobile/domain/models/store.model.dart';
 import 'package:immich_mobile/domain/models/user.model.dart';
+import 'package:immich_mobile/domain/services/user.service.dart';
 import 'package:immich_mobile/entities/album.entity.dart';
 import 'package:immich_mobile/entities/asset.entity.dart';
 import 'package:immich_mobile/entities/backup_album.entity.dart';
-import 'package:immich_mobile/entities/store.entity.dart';
 import 'package:immich_mobile/infrastructure/entities/user.entity.dart'
     as entity;
 import 'package:immich_mobile/interfaces/album.interface.dart';
@@ -21,6 +20,7 @@ import 'package:immich_mobile/interfaces/asset.interface.dart';
 import 'package:immich_mobile/interfaces/backup_album.interface.dart';
 import 'package:immich_mobile/models/albums/album_add_asset_response.model.dart';
 import 'package:immich_mobile/models/albums/album_search.model.dart';
+import 'package:immich_mobile/providers/infrastructure/user.provider.dart';
 import 'package:immich_mobile/repositories/album.repository.dart';
 import 'package:immich_mobile/repositories/album_api.repository.dart';
 import 'package:immich_mobile/repositories/album_media.repository.dart';
@@ -28,11 +28,13 @@ import 'package:immich_mobile/repositories/asset.repository.dart';
 import 'package:immich_mobile/repositories/backup.repository.dart';
 import 'package:immich_mobile/services/entity.service.dart';
 import 'package:immich_mobile/services/sync.service.dart';
+import 'package:immich_mobile/utils/hash.dart';
 import 'package:logging/logging.dart';
 
 final albumServiceProvider = Provider(
   (ref) => AlbumService(
     ref.watch(syncServiceProvider),
+    ref.watch(userServiceProvider),
     ref.watch(entityServiceProvider),
     ref.watch(albumRepositoryProvider),
     ref.watch(assetRepositoryProvider),
@@ -44,6 +46,7 @@ final albumServiceProvider = Provider(
 
 class AlbumService {
   final SyncService _syncService;
+  final UserService _userService;
   final EntityService _entityService;
   final IAlbumRepository _albumRepository;
   final IAssetRepository _assetRepository;
@@ -56,6 +59,7 @@ class AlbumService {
 
   AlbumService(
     this._syncService,
+    this._userService,
     this._entityService,
     this._albumRepository,
     this._assetRepository,
@@ -205,7 +209,7 @@ class AlbumService {
     final Album album = await _albumApiRepository.create(
       albumName,
       assetIds: assets.map((asset) => asset.remoteId!),
-      sharedUserIds: sharedUsers.map((user) => user.uid),
+      sharedUserIds: sharedUsers.map((user) => user.id),
     );
     await _entityService.fillAlbumWithDatabaseEntities(album);
     return _albumRepository.create(album);
@@ -292,8 +296,8 @@ class AlbumService {
 
   Future<bool> deleteAlbum(Album album) async {
     try {
-      final userId = Store.get(StoreKey.currentUser).id;
+      final userId = _userService.getMyUser().id;
-      if (album.owner.value?.isarId == userId) {
+      if (album.owner.value?.isarId == fastHash(userId)) {
         await _albumApiRepository.delete(album.remoteId!);
       }
       if (album.shared) {
@@ -359,7 +363,7 @@ class AlbumService {
     try {
       await _albumApiRepository.removeUser(
         album.remoteId!,
-        userId: user.uid,
+        userId: user.id,
       );
 
       album.sharedUsers.remove(entity.User.fromDto(user));

mobile/lib/services/api.service.dart

@@ -35,6 +35,9 @@ class ApiService implements Authentication {
   late MemoriesApi memoriesApi;
 
   ApiService() {
+    // The below line ensures that the api clients are initialized when the service is instantiated
+    // This is required to avoid late initialization errors when the clients are access before the endpoint is resolved
+    setEndpoint('');
     final endpoint = Store.tryGet(StoreKey.serverEndpoint);
     if (endpoint != null && endpoint.isNotEmpty) {
       setEndpoint(endpoint);

mobile/lib/services/asset.service.dart

@@ -6,9 +6,8 @@ import 'package:flutter/material.dart';
 import 'package:hooks_riverpod/hooks_riverpod.dart';
 import 'package:immich_mobile/domain/interfaces/exif.interface.dart';
 import 'package:immich_mobile/domain/interfaces/user.interface.dart';
-import 'package:immich_mobile/domain/models/store.model.dart';
 import 'package:immich_mobile/domain/models/user.model.dart';
-import 'package:immich_mobile/domain/services/store.service.dart';
+import 'package:immich_mobile/domain/services/user.service.dart';
 import 'package:immich_mobile/entities/asset.entity.dart';
 import 'package:immich_mobile/entities/backup_album.entity.dart';
 import 'package:immich_mobile/interfaces/asset.interface.dart';
@@ -19,9 +18,7 @@ import 'package:immich_mobile/interfaces/etag.interface.dart';
 import 'package:immich_mobile/models/backup/backup_candidate.model.dart';
 import 'package:immich_mobile/providers/api.provider.dart';
 import 'package:immich_mobile/providers/infrastructure/exif.provider.dart';
-import 'package:immich_mobile/providers/infrastructure/store.provider.dart';
+import 'package:immich_mobile/providers/infrastructure/user.provider.dart';
-import 'package:immich_mobile/providers/infrastructure/user.provider.dart'
-    hide userServiceProvider;
 import 'package:immich_mobile/repositories/asset.repository.dart';
 import 'package:immich_mobile/repositories/asset_api.repository.dart';
 import 'package:immich_mobile/repositories/asset_media.repository.dart';
@@ -47,7 +44,7 @@ final assetServiceProvider = Provider(
     ref.watch(syncServiceProvider),
     ref.watch(backupServiceProvider),
     ref.watch(albumServiceProvider),
-    ref.watch(storeServiceProvider),
+    ref.watch(userServiceProvider),
     ref.watch(assetMediaRepositoryProvider),
   ),
 );
@@ -63,7 +60,7 @@ class AssetService {
   final SyncService _syncService;
   final BackupService _backupService;
   final AlbumService _albumService;
-  final StoreService _storeService;
+  final UserService _userService;
   final IAssetMediaRepository _assetMediaRepository;
   final log = Logger('AssetService');
 
@@ -78,7 +75,7 @@ class AssetService {
     this._syncService,
     this._backupService,
     this._albumService,
-    this._storeService,
+    this._userService,
     this._assetMediaRepository,
   );
 
@@ -104,7 +101,7 @@ class AssetService {
       _getRemoteAssetChanges(List<UserDto> users, DateTime since) async {
     final dto = AssetDeltaSyncDto(
       updatedAfter: since,
-      userIds: users.map((e) => e.uid).toList(),
+      userIds: users.map((e) => e.id).toList(),
     );
     final changes = await _apiService.syncApi.getDeltaSync(dto);
     return changes == null || changes.needsFullSync
@@ -145,7 +142,7 @@ class AssetService {
           limit: chunkSize,
           updatedUntil: until,
           lastId: lastId,
-          userId: user.uid,
+          userId: user.id,
         );
         log.fine("Requesting $chunkSize assets from $lastId");
         final List<AssetResponseDto>? assets =
@@ -316,7 +313,7 @@ class AssetService {
       );
 
       await refreshRemoteAssets();
-      final owner = _storeService.get(StoreKey.currentUser);
+      final owner = _userService.getMyUser();
       final remoteAssets = await _assetRepository.getAll(
         ownerId: owner.id,
         state: AssetState.merged,
@@ -522,12 +519,12 @@ class AssetService {
   }
 
   Future<List<Asset>> getRecentlyAddedAssets() {
-    final me = _storeService.get(StoreKey.currentUser);
+    final me = _userService.getMyUser();
     return _assetRepository.getRecentlyAddedAssets(me.id);
   }
 
   Future<List<Asset>> getMotionAssets() {
-    final me = _storeService.get(StoreKey.currentUser);
+    final me = _userService.getMyUser();
     return _assetRepository.getMotionAssets(me.id);
   }
 }