feat: migrate to vitest

2024-03-15 14:46:08 -04:00
865 changed files with 15652 additions and 28757 deletions
@@ -45,7 +45,7 @@ jobs:
        uses: subosito/flutter-action@v2
        with:
          channel: "stable"
-          flutter-version: "3.19.3"
+          flutter-version: "3.16.9"
          cache: true

      - name: Create the Keystore
@@ -4,16 +4,16 @@ on:
  workflow_dispatch:
    inputs:
      serverBump:
-        description: 'Bump server version'
+        description: "Bump server version"
        required: true
-        default: 'false'
+        default: "false"
        type: choice
        options:
-          - 'false'
+          - "false"
          - minor
          - patch
      mobileBump:
-        description: 'Bump mobile build number'
+        description: "Bump mobile build number"
        required: false
        type: boolean

@@ -46,8 +46,8 @@ jobs:
        with:
          author_name: Alex The Bot
          author_email: alex.tran1502@gmail.com
-          default_author: user_info
-          message: 'Version ${{ env.IMMICH_VERSION }}'
+          default_author: user_info 
+          message: "Version ${{ env.IMMICH_VERSION }}"
          tag: ${{ env.IMMICH_VERSION }}
          push: true

@@ -85,5 +85,4 @@ jobs:
            docker/example.env
            docker/hwaccel.ml.yml
            docker/hwaccel.transcoding.yml
-            docker/prometheus.yml
            *.apk
@@ -23,7 +23,7 @@ jobs:
        uses: subosito/flutter-action@v2
        with:
          channel: "stable"
-          flutter-version: "3.19.3"
+          flutter-version: "3.16.9"

      - name: Install dependencies
        run: dart pub get
@@ -329,14 +329,14 @@ jobs:

      - name: Generate new migrations
        continue-on-error: true
-        run: npm run typeorm:migrations:generate ./src/migrations/TestMigration
+        run: npm run typeorm:migrations:generate ./src/infra/migrations/TestMigration

      - name: Find file changes
        uses: tj-actions/verify-changed-files@v19
        id: verify-changed-files
        with:
          files: |
-            server/src/migrations/
+            server/src/infra/migrations/
      - name: Verify migration files have not changed
        if: steps.verify-changed-files.outputs.files_changed == 'true'
        run: |
@@ -354,7 +354,7 @@ jobs:
        id: verify-changed-sql-files
        with:
          files: |
-            server/src/queries
+            server/src/infra/sql

      - name: Verify SQL files have not changed
        if: steps.verify-changed-sql-files.outputs.files_changed == 'true'
@@ -1,34 +0,0 @@
-{
-  "editor.formatOnSave": true,
-  "[javascript][typescript][css]": {
-    "editor.defaultFormatter": "esbenp.prettier-vscode",
-    "editor.tabSize": 2,
-    "editor.formatOnSave": true
-  },
-  "[svelte]": {
-    "editor.defaultFormatter": "svelte.svelte-vscode",
-    "editor.tabSize": 2
-  },
-  "svelte.enable-ts-plugin": true,
-  "eslint.validate": [
-    "javascript",
-    "svelte"
-  ],
-  "typescript.preferences.importModuleSpecifier": "non-relative",
-  "[dart]": {
-    "editor.formatOnSave": true,
-    "editor.selectionHighlight": false,
-    "editor.suggest.snippetsPreventQuickSuggestions": false,
-    "editor.suggestSelection": "first",
-    "editor.tabCompletion": "onlySnippets",
-    "editor.wordBasedSuggestions": "off",
-    "editor.defaultFormatter": "Dart-Code.dart-code"
-  },
-  "cSpell.words": [
-    "immich"
-  ],
-  "explorer.fileNesting.enabled": true,
-  "explorer.fileNesting.patterns": {
-    "*.ts": "${capture}.spec.ts,${capture}.mock.ts"
-  }
-}
@@ -11,24 +11,24 @@
 <p align="center">
 <img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
-<h3 align="center">High performance self-hosted photo and video management solution</h3>
+<h3 align="center">High performance self-hosted photo and video backup solution</h3>
 <br/>
 <a href="https://immich.app">
 <img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="readme_i18n/README_ca_ES.md">Català</a>
-  <a href="readme_i18n/README_es_ES.md">Español</a>
-  <a href="readme_i18n/README_fr_FR.md">Français</a>
-  <a href="readme_i18n/README_it_IT.md">Italiano</a>
-  <a href="readme_i18n/README_ja_JP.md">日本語</a>
-  <a href="readme_i18n/README_ko_KR.md">한국어</a>
-  <a href="readme_i18n/README_de_DE.md">Deutsch</a>
-  <a href="readme_i18n/README_nl_NL.md">Nederlands</a>
-  <a href="readme_i18n/README_tr_TR.md">Türkçe</a>
-  <a href="readme_i18n/README_zh_CN.md">中文</a>
-  <a href="readme_i18n/README_ru_RU.md">Русский</a>
+  <a href="README_ca_ES.md">Català</a>
+  <a href="README_es_ES.md">Español</a>
+  <a href="README_fr_FR.md">Français</a>
+  <a href="README_it_IT.md">Italiano</a>
+  <a href="README_ja_JP.md">日本語</a>
+  <a href="README_ko_KR.md">한국어</a>
+  <a href="README_de_DE.md">Deutsch</a>
+  <a href="README_nl_NL.md">Nederlands</a>
+  <a href="README_tr_TR.md">Türkçe</a>
+  <a href="README_zh_CN.md">中文</a>
+  <a href="README_ru_RU.md">Русский</a>
 </p>

 ## Disclaimer
@@ -131,10 +131,6 @@ If you feel like this is the right cause and the app is something you are seeing

 ## Star History

-<a href="https://star-history.com/#immich-app/immich&Date">
- <picture>
-   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=immich-app/immich&type=Date&theme=dark" />
-   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=immich-app/immich&type=Date" />
-   <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=immich-app/immich&type=Date" width="100%" />
- </picture>
+<a href="https://star-history.com/#immich-app/immich">
+  <img src="https://api.star-history.com/svg?repos=immich-app/immich&type=Date" alt="Star History Chart" width="100%" />
 </a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Iniciar sessió amb URL personalitzada">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Iniciar sessió amb URL personalitzada">
 </p>
 <h3 align="center">Immich - Solució de còpia de seguretat d'alta rendiment per a fotos i vídeos auto-allotjada</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Captura de pantalla principal">
+<img src="design/immich-screenshots.png" title="Captura de pantalla principal">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
  <a href="README_it_IT.md">Italiano</a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login mit eigener URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login mit eigener URL">
 </p>
 <h3 align="center">Immich - Hoch performante, selbst gehostete Backup-Lösung für Fotos und Videos</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Haupt-Screenshot">
+<img src="design/immich-screenshots.png" title="Haupt-Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Iniciar sesión con URL personalizada">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Iniciar sesión con URL personalizada">
 </p>
 <h3 align="center">Immich: Una solución Self-Hosted de copia de seguridad de fotos y videos de alto rendimiento</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Captura de pantalla principal">
+<img src="design/immich-screenshots.png" title="Captura de pantalla principal">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_fr_FR.md">Français</a>
  <a href="README_it_IT.md">Italiano</a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
 <h3 align="center">Immich - Solution de sauvegarde performante et auto-hébergée des photos et des vidéos</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Main Screenshot">
+<img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_it_IT.md">Italiano</a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
 <h3 align="center">Immich - Soluzione self-hosted ad alte prestazioni per backup di foto e video</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Main Screenshot">
+<img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
 <h3 align="center">Immich - 高性能なセルフホスト 写真/ビデオバックアップソリューション</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Main Screenshot">
+<img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
 <h3 align="center">Immich - 고성능 자체 호스팅 사진 및 동영상 백업 솔루션</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Main Screenshot">
+<img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login met aangepaste URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login met aangepaste URL">
 </p>
 <h3 align="center">Immich - Hoogwaardige, self-hosted back-up oplossing voor foto's en video's</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Main Screenshot">
+<img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
@@ -9,12 +9,12 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
 <h3 align="center">Immich - Высокопроизводительное решение для автономоного создания фото и видео архивов</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Main Screenshot">
+<img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
@@ -9,16 +9,16 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
 <h3 align="center">Immich - Yüksek performanslı, kendine ait barındırılan fotoğraf ve video yedekleme çözümü</h3>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="Main Screenshot">
+<img src="design/immich-screenshots.png" title="Main Screenshot">
 </a>
 <br/>
 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
@@ -9,7 +9,7 @@
 </p>

 <p align="center">
-<img src="../design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
+<img src="design/immich-logo-stacked-light.svg" width="300" title="Login With Custom URL">
 </p>
 <h3 align="center">Immich - 高性能的自托管照片和视频备份方案</h3>
 <p align="center">  
@@ -17,12 +17,12 @@
 </p>
 <br/>
 <a href="https://immich.app">
-<img src="../design/immich-screenshots.png" title="界面截图">
+<img src="design/immich-screenshots.png" title="界面截图">
 </a>
 <br/>

 <p align="center">
-  <a href="../README.md">English</a>
+  <a href="README.md">English</a>
  <a href="README_ca_ES.md">Català</a>
  <a href="README_es_ES.md">Español</a>
  <a href="README_fr_FR.md">Français</a>
@@ -73,22 +73,17 @@
 规格: 甲骨文免费虚拟机套餐——阿姆斯特丹 4核 2.4Ghz ARM64 CPU, 24GB RAM。
 ```

-## 活跃度
-![活跃度](https://repobeats.axiom.co/api/embed/9e86d9dc3ddd137161f2f6d2e758d7863b1789cb.svg "Repobeats analytics image")
-
 # 功能特性

-
 | 功能特性                                    | 移动端 | 网页端 |
 |---------------------------------------------|--------|--------|
 | 上传并查看照片和视频                        | 是     | 是     |
 | 软件运行时自动备份                          | 是     | N/A    |
-| 忽略重复的项目                              | 是     | 是     |
 | 选择需要备份的相册                          | 是     | N/A    |
 | 下载照片和视频到本地                        | 是     | 是     |
 | 多用户支持                                  | 是     | 是     |
 | 相册与共享相册                              | 是     | 是     |
-| 可拖动的快速滚动条                          | 是     | 是     |
+| 可拖动的快速导航栏                          | 是     | 是     |
 | 支持RAW格式                                 | 是     | 是     |
 | 元数据视图（EXIF、地图）                    | 是     | 是     |
 | 通过元数据、对象、人脸和标签进行搜索        | 是     | 是     |
@@ -98,7 +93,6 @@
 | OAuth 支持                                  | 是     | 是     |
 | API Keys                                    | N/A    | 是     |
 | 实况照片备份和查看                          | 是     | 是     |
-| 支持360度全景图显示                         | 否     | 是     |
 | 用户自定义存储结构                          | 是     | 是     |
 | 公共分享                                    | 否     | 是     |
 | 归档与收藏功能                              | 是     | 是     |
@@ -110,6 +104,7 @@
 | 只读相册                                    | 是     | 是     |
 | 照片堆叠                                    | 是     | 是     |

+
 # 支持本项目

 我已经致力于本项目并且我将会持续更新文档、新增功能和修复问题。但是独木不成林，我需要您给予我坚持下去的动力。
@@ -131,13 +126,3 @@
 <a href="https://github.com/alextran1502/immich/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=immich-app/immich" width="100%"/>
 </a>
-
-## Star增长曲线
-
-<a href="https://star-history.com/#immich-app/immich&Date">
- <picture>
-   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=immich-app/immich&type=Date&theme=dark" />
-   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=immich-app/immich&type=Date" />
-   <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=immich-app/immich&type=Date" width="100%" />
- </picture>
-</a>
@@ -1,4 +1,4 @@
-FROM node:20-alpine3.19@sha256:bf77dc26e48ea95fca9d1aceb5acfa69d2e546b765ec2abfb502975f1a2d4def as core
+FROM node:20-alpine3.19@sha256:c0a3badbd8a0a760de903e00cedbca94588e609299820557e72cba2a53dbaa2c as core

 WORKDIR /usr/src/open-api/typescript-sdk
 COPY open-api/typescript-sdk/package*.json open-api/typescript-sdk/tsconfig*.json ./
@@ -1,12 +1,12 @@
 {
  "name": "@immich/cli",
-  "version": "2.2.0",
+  "version": "2.1.0",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@immich/cli",
-      "version": "2.2.0",
+      "version": "2.1.0",
      "license": "GNU Affero General Public License version 3",
      "dependencies": {
        "lodash-es": "^4.17.21"
@@ -47,7 +47,7 @@
    },
    "../open-api/typescript-sdk": {
      "name": "@immich/sdk",
-      "version": "1.100.0",
+      "version": "1.98.2",
      "dev": true,
      "license": "GNU Affero General Public License version 3",
      "dependencies": {
@@ -300,9 +300,9 @@
      "dev": true
    },
    "node_modules/@esbuild/aix-ppc64": {
-      "version": "0.20.2",
-      "resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.20.2.tgz",
-      "integrity": "sha512-D+EBOJHXdNZcLJRBkhENNG8Wji2kgc9AZ9KiPr1JuZjsNtyHzrsfLRrY0tk2H2aoFu6RANO1y1iPPUCDYWkb5g==",
+      "version": "0.19.12",
+      "resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.19.12.tgz",
+      "integrity": "sha512-bmoCYyWdEL3wDQIVbcyzRyeKLgk2WtWLTWz1ZIAZF/EGbNOwSA6ew3PftJ1PqMiOOGu0OyFMzG53L0zqIpPeNA==",
      "cpu": [
        "ppc64"
      ],
@@ -316,9 +316,9 @@
      }
    },
    "node_modules/@esbuild/android-arm": {
-      "version": "0.20.2",
-      "resolved": "https://registry.npmjs.org/@esbuild/android-arm/-/android-arm-0.20.2.tgz",
-      "integrity": "sha512-t98Ra6pw2VaDhqNWO2Oph2LXbz/EJcnLmKLGBJwEwXX/JAN83Fym1rU8l0JUWK6HkIbWONCSSatf4sf2NBRx/w==",
+      "version": "0.19.12",
+      "resolved": "https://registry.npmjs.org/@esbuild/android-arm/-/android-arm-0.19.12.tgz",
+      "integrity": "sha512-qg/Lj1mu3CdQlDEEiWrlC4eaPZ1KztwGJ9B6J+/6G+/4ewxJg7gqj8eVYWvao1bXrqGiW2rsBZFSX3q2lcW05w==",
      "cpu": [
        "arm"
      ],
@@ -332,9 +332,9 @@
      }
    },
    "node_modules/@esbuild/android-arm64": {
-      "version": "0.20.2",
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    "node_modules/typescript": {
-      "version": "5.4.3",
-      "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.4.3.tgz",
-      "integrity": "sha512-KrPd3PKaCLr78MalgiwJnA25Nm8HAmdwN3mYUYZgG/wizIo9EainNVQI9/yDavtVFRN2h3k8uf3GLHuhDMgEHg==",
+      "version": "5.4.2",
+      "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.4.2.tgz",
+      "integrity": "sha512-+2/g0Fds1ERlP6JsakQQDXjZdZMM+rqpamFZJEKh4kwTIn3iDkgKtby0CeNd5ATNZ4Ry1ax15TMx0W2V+miizQ==",
      "dev": true,
      "bin": {
        "tsc": "bin/tsc",
@@ -4456,14 +4464,14 @@
      }
    },
    "node_modules/vite": {
-      "version": "5.2.3",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-5.2.3.tgz",
-      "integrity": "sha512-+i1oagbvkVIhEy9TnEV+fgXsng13nZM90JQbrcPrf6DvW2mXARlz+DK7DLiDP+qeKoD1FCVx/1SpFL1CLq9Mhw==",
+      "version": "5.1.6",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-5.1.6.tgz",
+      "integrity": "sha512-yYIAZs9nVfRJ/AiOLCA91zzhjsHUgMjB+EigzFb6W2XTLO8JixBCKCjvhKZaye+NKYHCrkv3Oh50dH9EdLU2RA==",
      "dev": true,
      "dependencies": {
-        "esbuild": "^0.20.1",
-        "postcss": "^8.4.36",
-        "rollup": "^4.13.0"
+        "esbuild": "^0.19.3",
+        "postcss": "^8.4.35",
+        "rollup": "^4.2.0"
      },
      "bin": {
        "vite": "bin/vite.js"
@@ -4511,9 +4519,9 @@
      }
    },
    "node_modules/vite-node": {
-      "version": "1.4.0",
-      "resolved": "https://registry.npmjs.org/vite-node/-/vite-node-1.4.0.tgz",
-      "integrity": "sha512-VZDAseqjrHgNd4Kh8icYHWzTKSCZMhia7GyHfhtzLW33fZlG9SwsB6CEhgyVOWkJfJ2pFLrp/Gj1FSfAiqH9Lw==",
+      "version": "1.3.1",
+      "resolved": "https://registry.npmjs.org/vite-node/-/vite-node-1.3.1.tgz",
+      "integrity": "sha512-azbRrqRxlWTJEVbzInZCTchx0X69M/XPTCz4H+TLvlTcR/xH/3hkRqhOakT41fMJCMzXTu4UvegkZiEoJAWvng==",
      "dev": true,
      "dependencies": {
        "cac": "^6.7.14",
@@ -4552,16 +4560,16 @@
      }
    },
    "node_modules/vitest": {
-      "version": "1.4.0",
-      "resolved": "https://registry.npmjs.org/vitest/-/vitest-1.4.0.tgz",
-      "integrity": "sha512-gujzn0g7fmwf83/WzrDTnncZt2UiXP41mHuFYFrdwaLRVQ6JYQEiME2IfEjU3vcFL3VKa75XhI3lFgn+hfVsQw==",
+      "version": "1.3.1",
+      "resolved": "https://registry.npmjs.org/vitest/-/vitest-1.3.1.tgz",
+      "integrity": "sha512-/1QJqXs8YbCrfv/GPQ05wAZf2eakUPLPa18vkJAKE7RXOKfVHqMZZ1WlTjiwl6Gcn65M5vpNUB6EFLnEdRdEXQ==",
      "dev": true,
      "dependencies": {
-        "@vitest/expect": "1.4.0",
-        "@vitest/runner": "1.4.0",
-        "@vitest/snapshot": "1.4.0",
-        "@vitest/spy": "1.4.0",
-        "@vitest/utils": "1.4.0",
+        "@vitest/expect": "1.3.1",
+        "@vitest/runner": "1.3.1",
+        "@vitest/snapshot": "1.3.1",
+        "@vitest/spy": "1.3.1",
+        "@vitest/utils": "1.3.1",
        "acorn-walk": "^8.3.2",
        "chai": "^4.3.10",
        "debug": "^4.3.4",
@@ -4575,7 +4583,7 @@
        "tinybench": "^2.5.1",
        "tinypool": "^0.8.2",
        "vite": "^5.0.0",
-        "vite-node": "1.4.0",
+        "vite-node": "1.3.1",
        "why-is-node-running": "^2.2.2"
      },
      "bin": {
@@ -4590,8 +4598,8 @@
      "peerDependencies": {
        "@edge-runtime/vm": "*",
        "@types/node": "^18.0.0 || >=20.0.0",
-        "@vitest/browser": "1.4.0",
-        "@vitest/ui": "1.4.0",
+        "@vitest/browser": "1.3.1",
+        "@vitest/ui": "1.3.1",
        "happy-dom": "*",
        "jsdom": "*"
      },
@@ -1,6 +1,6 @@
 {
  "name": "@immich/cli",
-  "version": "2.2.0",
+  "version": "2.1.0",
  "description": "Command Line Interface (CLI) for Immich",
  "type": "module",
  "exports": "./dist/index.js",
@@ -1,7 +1,5 @@
 import {
-  Action,
  AssetBulkUploadCheckResult,
-  AssetFileUploadResponseDto,
  addAssetsToAlbum,
  checkBulkUpload,
  createAlbum,
@@ -10,320 +8,445 @@ import {
  getSupportedMediaTypes,
 } from '@immich/sdk';
 import byteSize from 'byte-size';
-import { Presets, SingleBar } from 'cli-progress';
-import { chunk } from 'lodash-es';
-import { Stats, createReadStream } from 'node:fs';
-import { stat, unlink } from 'node:fs/promises';
+import cliProgress from 'cli-progress';
+import { chunk, zip } from 'lodash-es';
+import { createHash } from 'node:crypto';
+import fs, { createReadStream } from 'node:fs';
+import { access, constants, stat, unlink } from 'node:fs/promises';
 import os from 'node:os';
-import path, { basename } from 'node:path';
-import { BaseOptions, authenticate, crawl, sha1 } from 'src/utils';
+import { basename } from 'node:path';
+import { CrawlService } from 'src/services/crawl.service';
+import { BaseOptions, authenticate } from 'src/utils';

-const s = (count: number) => (count === 1 ? '' : 's');
+const zipDefined = zip as <T, U>(a: T[], b: U[]) => [T, U][];

-// TODO figure out why `id` is missing
-type AssetBulkUploadCheckResults = Array<AssetBulkUploadCheckResult & { id: string }>;
-type Asset = { id: string; filepath: string };
+enum CheckResponseStatus {
+  ACCEPT = 'accept',
+  REJECT = 'reject',
+  DUPLICATE = 'duplicate',
+}

-interface UploadOptionsDto {
-  recursive?: boolean;
-  exclusionPatterns?: string[];
-  dryRun?: boolean;
-  skipHash?: boolean;
-  delete?: boolean;
-  album?: boolean;
+class Asset {
+  readonly path: string;
+
+  id?: string;
+  deviceAssetId?: string;
+  fileCreatedAt?: Date;
+  fileModifiedAt?: Date;
+  sidecarPath?: string;
+  fileSize?: number;
  albumName?: string;
-  includeHidden?: boolean;
-  concurrency: number;
-}

-class UploadFile extends File {
-  constructor(
-    private filepath: string,
-    private _size: number,
-  ) {
-    super([], basename(filepath));
+  constructor(path: string) {
+    this.path = path;
  }

-  get size() {
-    return this._size;
+  async prepare() {
+    const stats = await stat(this.path);
+    this.deviceAssetId = `${basename(this.path)}-${stats.size}`.replaceAll(/\s+/g, '');
+    this.fileCreatedAt = stats.mtime;
+    this.fileModifiedAt = stats.mtime;
+    this.fileSize = stats.size;
+    this.albumName = this.extractAlbumName();
  }

-  stream() {
-    return createReadStream(this.filepath) as any;
+  async getUploadFormData(): Promise<FormData> {
+    if (!this.deviceAssetId) {
+      throw new Error('Device asset id not set');
+    }
+    if (!this.fileCreatedAt) {
+      throw new Error('File created at not set');
+    }
+    if (!this.fileModifiedAt) {
+      throw new Error('File modified at not set');
+    }
+
+    // TODO: doesn't xmp replace the file extension? Will need investigation
+    const sideCarPath = `${this.path}.xmp`;
+    let sidecarData: Blob | undefined = undefined;
+    try {
+      await access(sideCarPath, constants.R_OK);
+      sidecarData = new File([await fs.openAsBlob(sideCarPath)], basename(sideCarPath));
+    } catch {}
+
+    const data: any = {
+      assetData: new File([await fs.openAsBlob(this.path)], basename(this.path)),
+      deviceAssetId: this.deviceAssetId,
+      deviceId: 'CLI',
+      fileCreatedAt: this.fileCreatedAt.toISOString(),
+      fileModifiedAt: this.fileModifiedAt.toISOString(),
+      isFavorite: String(false),
+    };
+    const formData = new FormData();
+
+    for (const property in data) {
+      formData.append(property, data[property]);
+    }
+
+    if (sidecarData) {
+      formData.append('sidecarData', sidecarData);
+    }
+
+    return formData;
+  }
+
+  async delete(): Promise<void> {
+    return unlink(this.path);
+  }
+
+  public async hash(): Promise<string> {
+    const sha1 = (filePath: string) => {
+      const hash = createHash('sha1');
+      return new Promise<string>((resolve, reject) => {
+        const rs = createReadStream(filePath);
+        rs.on('error', reject);
+        rs.on('data', (chunk) => hash.update(chunk));
+        rs.on('end', () => resolve(hash.digest('hex')));
+      });
+    };
+
+    return await sha1(this.path);
+  }
+
+  private extractAlbumName(): string | undefined {
+    return os.platform() === 'win32' ? this.path.split('\\').at(-2) : this.path.split('/').at(-2);
  }
 }

-export const upload = async (paths: string[], baseOptions: BaseOptions, options: UploadOptionsDto) => {
-  await authenticate(baseOptions);
+class UploadOptionsDto {
+  recursive? = false;
+  exclusionPatterns?: string[] = [];
+  dryRun? = false;
+  skipHash? = false;
+  delete? = false;
+  album? = false;
+  albumName? = '';
+  includeHidden? = false;
+  concurrency? = 4;
+}

-  const files = await scan(paths, options);
-  if (files.length === 0) {
-    console.log('No files found, exiting');
-    return;
+export const upload = (paths: string[], baseOptions: BaseOptions, uploadOptions: UploadOptionsDto) =>
+  new UploadCommand().run(paths, baseOptions, uploadOptions);
+
+// TODO refactor this
+class UploadCommand {
+  public async run(paths: string[], baseOptions: BaseOptions, options: UploadOptionsDto): Promise<void> {
+    await authenticate(baseOptions);
+
+    console.log('Crawling for assets...');
+    const files = await this.getFiles(paths, options);
+
+    if (files.length === 0) {
+      console.log('No assets found, exiting');
+      return;
+    }
+
+    const assetsToCheck = files.map((path) => new Asset(path));
+
+    const { newAssets, duplicateAssets } = await this.checkAssets(assetsToCheck, options.concurrency ?? 4);
+
+    const totalSizeUploaded = await this.upload(newAssets, options);
+    const messageStart = options.dryRun ? 'Would have' : 'Successfully';
+    if (newAssets.length === 0) {
+      console.log('All assets were already uploaded, nothing to do.');
+    } else {
+      console.log(
+        `${messageStart} uploaded ${newAssets.length} asset${newAssets.length === 1 ? '' : 's'} (${byteSize(totalSizeUploaded)})`,
+      );
+    }
+
+    if (options.album || options.albumName) {
+      const { createdAlbumCount, updatedAssetCount } = await this.updateAlbums(
+        [...newAssets, ...duplicateAssets],
+        options,
+      );
+      console.log(`${messageStart} created ${createdAlbumCount} new album${createdAlbumCount === 1 ? '' : 's'}`);
+      console.log(`${messageStart} updated ${updatedAssetCount} asset${updatedAssetCount === 1 ? '' : 's'}`);
+    }
+
+    if (!options.delete) {
+      return;
+    }
+
+    if (options.dryRun) {
+      console.log(`Would now have deleted assets, but skipped due to dry run`);
+      return;
+    }
+
+    console.log('Deleting assets that have been uploaded...');
+
+    await this.deleteAssets(newAssets, options);
  }

-  const { newFiles, duplicates } = await checkForDuplicates(files, options);
+  public async checkAssets(
+    assetsToCheck: Asset[],
+    concurrency: number,
+  ): Promise<{ newAssets: Asset[]; duplicateAssets: Asset[]; rejectedAssets: Asset[] }> {
+    for (const assets of chunk(assetsToCheck, concurrency)) {
+      await Promise.all(assets.map((asset: Asset) => asset.prepare()));
+    }

-  const newAssets = await uploadFiles(newFiles, options);
-  await updateAlbums([...newAssets, ...duplicates], options);
-  await deleteFiles(newFiles, options);
-};
+    const checkProgress = new cliProgress.SingleBar(
+      { format: 'Checking assets | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} assets' },
+      cliProgress.Presets.shades_classic,
+    );
+    checkProgress.start(assetsToCheck.length, 0);

-const scan = async (pathsToCrawl: string[], options: UploadOptionsDto) => {
-  const { image, video } = await getSupportedMediaTypes();
-
-  console.log('Crawling for assets...');
-  const files = await crawl({
-    pathsToCrawl,
-    recursive: options.recursive,
-    exclusionPatterns: options.exclusionPatterns,
-    includeHidden: options.includeHidden,
-    extensions: [...image, ...video],
-  });
-
-  return files;
-};
-
-const checkForDuplicates = async (files: string[], { concurrency }: UploadOptionsDto) => {
-  const progressBar = new SingleBar(
-    { format: 'Checking files | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} assets' },
-    Presets.shades_classic,
-  );
-
-  progressBar.start(files.length, 0);
-
-  const newFiles: string[] = [];
-  const duplicates: Asset[] = [];
-
-  try {
-    // TODO refactor into a queue
-    for (const items of chunk(files, concurrency)) {
-      const dto = await Promise.all(items.map(async (filepath) => ({ id: filepath, checksum: await sha1(filepath) })));
-      const { results } = await checkBulkUpload({ assetBulkUploadCheckDto: { assets: dto } });
-
-      for (const { id: filepath, assetId, action } of results as AssetBulkUploadCheckResults) {
-        if (action === Action.Accept) {
-          newFiles.push(filepath);
-        } else {
-          // rejects are always duplicates
-          duplicates.push({ id: assetId as string, filepath });
+    const newAssets = [];
+    const duplicateAssets = [];
+    const rejectedAssets = [];
+    try {
+      for (const assets of chunk(assetsToCheck, concurrency)) {
+        const checkedAssets = await this.getStatus(assets);
+        for (const checked of checkedAssets) {
+          if (checked.status === CheckResponseStatus.ACCEPT) {
+            newAssets.push(checked.asset);
+          } else if (checked.status === CheckResponseStatus.DUPLICATE) {
+            duplicateAssets.push(checked.asset);
+          } else {
+            rejectedAssets.push(checked.asset);
+          }
+          checkProgress.increment();
        }
-        progressBar.increment();
+      }
+    } finally {
+      checkProgress.stop();
+    }
+
+    return { newAssets, duplicateAssets, rejectedAssets };
+  }
+
+  public async upload(assetsToUpload: Asset[], options: UploadOptionsDto): Promise<number> {
+    let totalSize = 0;
+
+    // Compute total size first
+    for (const asset of assetsToUpload) {
+      totalSize += asset.fileSize ?? 0;
+    }
+
+    if (options.dryRun) {
+      return totalSize;
+    }
+
+    const uploadProgress = new cliProgress.SingleBar(
+      {
+        format: 'Uploading assets | {bar} | {percentage}% | ETA: {eta_formatted} | {value_formatted}/{total_formatted}',
+      },
+      cliProgress.Presets.shades_classic,
+    );
+    uploadProgress.start(totalSize, 0);
+    uploadProgress.update({ value_formatted: 0, total_formatted: byteSize(totalSize) });
+
+    let totalSizeUploaded = 0;
+    try {
+      for (const assets of chunk(assetsToUpload, options.concurrency)) {
+        const ids = await this.uploadAssets(assets);
+        for (const [asset, id] of zipDefined(assets, ids)) {
+          asset.id = id;
+          if (asset.fileSize) {
+            totalSizeUploaded += asset.fileSize ?? 0;
+          } else {
+            console.log(`Could not determine file size for ${asset.path}`);
+          }
+        }
+        uploadProgress.update(totalSizeUploaded, { value_formatted: byteSize(totalSizeUploaded) });
+      }
+    } finally {
+      uploadProgress.stop();
+    }
+
+    return totalSizeUploaded;
+  }
+
+  public async getFiles(paths: string[], options: UploadOptionsDto): Promise<string[]> {
+    const inputFiles: string[] = [];
+    for (const pathArgument of paths) {
+      const fileStat = await fs.promises.lstat(pathArgument);
+      if (fileStat.isFile()) {
+        inputFiles.push(pathArgument);
      }
    }
-  } finally {
-    progressBar.stop();
+
+    const files: string[] = await this.crawl(paths, options);
+    files.push(...inputFiles);
+    return files;
  }

-  console.log(`Found ${newFiles.length} new files and ${duplicates.length} duplicate${s(duplicates.length)}`);
+  public async getAlbums(): Promise<Map<string, string>> {
+    const existingAlbums = await getAllAlbums({});

-  return { newFiles, duplicates };
-};
-
-const uploadFiles = async (files: string[], { dryRun, concurrency }: UploadOptionsDto): Promise<Asset[]> => {
-  if (files.length === 0) {
-    console.log('All assets were already uploaded, nothing to do.');
-    return [];
-  }
-
-  // Compute total size first
-  let totalSize = 0;
-  const statsMap = new Map<string, Stats>();
-  for (const filepath of files) {
-    const stats = await stat(filepath);
-    statsMap.set(filepath, stats);
-    totalSize += stats.size;
-  }
-
-  if (dryRun) {
-    console.log(`Would have uploaded ${files.length} asset${s(files.length)} (${byteSize(totalSize)})`);
-    return [];
-  }
-
-  const uploadProgress = new SingleBar(
-    { format: 'Uploading assets | {bar} | {percentage}% | ETA: {eta_formatted} | {value_formatted}/{total_formatted}' },
-    Presets.shades_classic,
-  );
-  uploadProgress.start(totalSize, 0);
-  uploadProgress.update({ value_formatted: 0, total_formatted: byteSize(totalSize) });
-
-  let totalSizeUploaded = 0;
-  const newAssets: Asset[] = [];
-  try {
-    for (const items of chunk(files, concurrency)) {
-      await Promise.all(
-        items.map(async (filepath) => {
-          const stats = statsMap.get(filepath) as Stats;
-          const response = await uploadFile(filepath, stats);
-          totalSizeUploaded += stats.size ?? 0;
-          uploadProgress.update(totalSizeUploaded, { value_formatted: byteSize(totalSizeUploaded) });
-          newAssets.push({ id: response.id, filepath });
-          return response;
-        }),
-      );
+    const albumMapping = new Map<string, string>();
+    for (const album of existingAlbums) {
+      albumMapping.set(album.albumName, album.id);
    }
-  } finally {
-    uploadProgress.stop();
+
+    return albumMapping;
  }

-  console.log(`Successfully uploaded ${newAssets.length} asset${s(newAssets.length)} (${byteSize(totalSizeUploaded)})`);
-  return newAssets;
-};
-
-const uploadFile = async (input: string, stats: Stats): Promise<AssetFileUploadResponseDto> => {
-  const { baseUrl, headers } = defaults;
-
-  const assetPath = path.parse(input);
-  const noExtension = path.join(assetPath.dir, assetPath.name);
-
-  const sidecarsFiles = await Promise.all(
-    // XMP sidecars can come in two filename formats. For a photo named photo.ext, the filenames are photo.ext.xmp and photo.xmp
-    [`${noExtension}.xmp`, `${input}.xmp`].map(async (sidecarPath) => {
-      try {
-        const stats = await stat(sidecarPath);
-        return new UploadFile(sidecarPath, stats.size);
-      } catch {
-        return false;
-      }
-    }),
-  );
-
-  const sidecarData = sidecarsFiles.find((file): file is UploadFile => file !== false);
-
-  const formData = new FormData();
-  formData.append('deviceAssetId', `${basename(input)}-${stats.size}`.replaceAll(/\s+/g, ''));
-  formData.append('deviceId', 'CLI');
-  formData.append('fileCreatedAt', stats.mtime.toISOString());
-  formData.append('fileModifiedAt', stats.mtime.toISOString());
-  formData.append('fileSize', String(stats.size));
-  formData.append('isFavorite', 'false');
-  formData.append('assetData', new UploadFile(input, stats.size));
-
-  if (sidecarData) {
-    formData.append('sidecarData', sidecarData);
-  }
-
-  const response = await fetch(`${baseUrl}/asset/upload`, {
-    method: 'post',
-    redirect: 'error',
-    headers: headers as Record<string, string>,
-    body: formData,
-  });
-  if (response.status !== 200 && response.status !== 201) {
-    throw new Error(await response.text());
-  }
-
-  return response.json();
-};
-
-const deleteFiles = async (files: string[], options: UploadOptionsDto): Promise<void> => {
-  if (!options.delete) {
-    return;
-  }
-
-  if (options.dryRun) {
-    console.log(`Would now have deleted assets, but skipped due to dry run`);
-    return;
-  }
-
-  console.log('Deleting assets that have been uploaded...');
-
-  const deletionProgress = new SingleBar(
-    { format: 'Deleting local assets | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} assets' },
-    Presets.shades_classic,
-  );
-  deletionProgress.start(files.length, 0);
-
-  try {
-    for (const assetBatch of chunk(files, options.concurrency)) {
-      await Promise.all(assetBatch.map((input: string) => unlink(input)));
-      deletionProgress.update(assetBatch.length);
-    }
-  } finally {
-    deletionProgress.stop();
-  }
-};
-
-const updateAlbums = async (assets: Asset[], options: UploadOptionsDto) => {
-  if (!options.album && !options.albumName) {
-    return;
-  }
-  const { dryRun, concurrency } = options;
-
-  const albums = await getAllAlbums({});
-  const existingAlbums = new Map(albums.map((album) => [album.albumName, album.id]));
-  const newAlbums: Set<string> = new Set();
-  for (const { filepath } of assets) {
-    const albumName = getAlbumName(filepath, options);
-    if (albumName && !existingAlbums.has(albumName)) {
-      newAlbums.add(albumName);
-    }
-  }
-
-  if (dryRun) {
-    // TODO print asset counts for new albums
-    console.log(`Would have created ${newAlbums.size} new album${s(newAlbums.size)}`);
-    console.log(`Would have updated ${assets.length} asset${s(assets.length)}`);
-    return;
-  }
-
-  const progressBar = new SingleBar(
-    { format: 'Creating albums | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} albums' },
-    Presets.shades_classic,
-  );
-  progressBar.start(newAlbums.size, 0);
-
-  try {
-    for (const albumNames of chunk([...newAlbums], concurrency)) {
-      const items = await Promise.all(
-        albumNames.map((albumName: string) => createAlbum({ createAlbumDto: { albumName } })),
-      );
-      for (const { id, albumName } of items) {
-        existingAlbums.set(albumName, id);
-      }
-      progressBar.increment(albumNames.length);
-    }
-  } finally {
-    progressBar.stop();
-  }
-
-  console.log(`Successfully created ${newAlbums.size} new album${s(newAlbums.size)}`);
-  console.log(`Successfully updated ${assets.length} asset${s(assets.length)}`);
-
-  const albumToAssets = new Map<string, string[]>();
-  for (const asset of assets) {
-    const albumName = getAlbumName(asset.filepath, options);
-    if (!albumName) {
-      continue;
-    }
-    const albumId = existingAlbums.get(albumName);
-    if (albumId) {
-      if (!albumToAssets.has(albumId)) {
-        albumToAssets.set(albumId, []);
-      }
-      albumToAssets.get(albumId)?.push(asset.id);
-    }
-  }
-
-  const albumUpdateProgress = new SingleBar(
-    { format: 'Adding assets to albums | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} assets' },
-    Presets.shades_classic,
-  );
-  albumUpdateProgress.start(assets.length, 0);
-
-  try {
-    for (const [albumId, assets] of albumToAssets.entries()) {
-      for (const assetBatch of chunk(assets, Math.min(1000 * concurrency, 65_000))) {
-        await addAssetsToAlbum({ id: albumId, bulkIdsDto: { ids: assetBatch } });
-        albumUpdateProgress.increment(assetBatch.length);
+  public async updateAlbums(
+    assets: Asset[],
+    options: UploadOptionsDto,
+  ): Promise<{ createdAlbumCount: number; updatedAssetCount: number }> {
+    if (options.albumName) {
+      for (const asset of assets) {
+        asset.albumName = options.albumName;
      }
    }
-  } finally {
-    albumUpdateProgress.stop();
-  }
-};

-const getAlbumName = (filepath: string, options: UploadOptionsDto) => {
-  const folderName = os.platform() === 'win32' ? filepath.split('\\').at(-2) : filepath.split('/').at(-2);
-  return options.albumName ?? folderName;
-};
+    const existingAlbums = await this.getAlbums();
+    const assetsToUpdate = assets.filter(
+      (asset): asset is Asset & { albumName: string; id: string } => !!(asset.albumName && asset.id),
+    );
+
+    const newAlbumsSet: Set<string> = new Set();
+    for (const asset of assetsToUpdate) {
+      if (!existingAlbums.has(asset.albumName)) {
+        newAlbumsSet.add(asset.albumName);
+      }
+    }
+
+    const newAlbums = [...newAlbumsSet];
+
+    if (options.dryRun) {
+      return { createdAlbumCount: newAlbums.length, updatedAssetCount: assetsToUpdate.length };
+    }
+
+    const albumCreationProgress = new cliProgress.SingleBar(
+      {
+        format: 'Creating albums | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} albums',
+      },
+      cliProgress.Presets.shades_classic,
+    );
+    albumCreationProgress.start(newAlbums.length, 0);
+
+    try {
+      for (const albumNames of chunk(newAlbums, options.concurrency)) {
+        const newAlbumIds = await Promise.all(
+          albumNames.map((albumName: string) => createAlbum({ createAlbumDto: { albumName } }).then((r) => r.id)),
+        );
+
+        for (const [albumName, albumId] of zipDefined(albumNames, newAlbumIds)) {
+          existingAlbums.set(albumName, albumId);
+        }
+
+        albumCreationProgress.increment(albumNames.length);
+      }
+    } finally {
+      albumCreationProgress.stop();
+    }
+
+    const albumToAssets = new Map<string, string[]>();
+    for (const asset of assetsToUpdate) {
+      const albumId = existingAlbums.get(asset.albumName);
+      if (albumId) {
+        if (!albumToAssets.has(albumId)) {
+          albumToAssets.set(albumId, []);
+        }
+        albumToAssets.get(albumId)?.push(asset.id);
+      }
+    }
+
+    const albumUpdateProgress = new cliProgress.SingleBar(
+      {
+        format: 'Adding assets to albums | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} assets',
+      },
+      cliProgress.Presets.shades_classic,
+    );
+    albumUpdateProgress.start(assetsToUpdate.length, 0);
+
+    try {
+      for (const [albumId, assets] of albumToAssets.entries()) {
+        for (const assetBatch of chunk(assets, Math.min(1000 * (options.concurrency ?? 4), 65_000))) {
+          await addAssetsToAlbum({ id: albumId, bulkIdsDto: { ids: assetBatch } });
+          albumUpdateProgress.increment(assetBatch.length);
+        }
+      }
+    } finally {
+      albumUpdateProgress.stop();
+    }
+
+    return { createdAlbumCount: newAlbums.length, updatedAssetCount: assetsToUpdate.length };
+  }
+
+  public async deleteAssets(assets: Asset[], options: UploadOptionsDto): Promise<void> {
+    const deletionProgress = new cliProgress.SingleBar(
+      {
+        format: 'Deleting local assets | {bar} | {percentage}% | ETA: {eta}s | {value}/{total} assets',
+      },
+      cliProgress.Presets.shades_classic,
+    );
+    deletionProgress.start(assets.length, 0);
+
+    try {
+      for (const assetBatch of chunk(assets, options.concurrency)) {
+        await Promise.all(assetBatch.map((asset: Asset) => asset.delete()));
+        deletionProgress.update(assetBatch.length);
+      }
+    } finally {
+      deletionProgress.stop();
+    }
+  }
+
+  private async getStatus(assets: Asset[]): Promise<{ asset: Asset; status: CheckResponseStatus }[]> {
+    const checkResponse = await this.checkHashes(assets);
+
+    const responses = [];
+    for (const [check, asset] of zipDefined(checkResponse, assets)) {
+      if (check.assetId) {
+        asset.id = check.assetId;
+      }
+
+      if (check.action === 'accept') {
+        responses.push({ asset, status: CheckResponseStatus.ACCEPT });
+      } else if (check.reason === 'duplicate') {
+        responses.push({ asset, status: CheckResponseStatus.DUPLICATE });
+      } else {
+        responses.push({ asset, status: CheckResponseStatus.REJECT });
+      }
+    }
+
+    return responses;
+  }
+
+  private async checkHashes(assetsToCheck: Asset[]): Promise<AssetBulkUploadCheckResult[]> {
+    const checksums = await Promise.all(assetsToCheck.map((asset) => asset.hash()));
+    const assetBulkUploadCheckDto = {
+      assets: zipDefined(assetsToCheck, checksums).map(([asset, checksum]) => ({ id: asset.path, checksum })),
+    };
+    const checkResponse = await checkBulkUpload({ assetBulkUploadCheckDto });
+    return checkResponse.results;
+  }
+
+  private async uploadAssets(assets: Asset[]): Promise<string[]> {
+    const fileRequests = await Promise.all(assets.map((asset) => asset.getUploadFormData()));
+    const results = await Promise.all(fileRequests.map((request) => this.uploadAsset(request)));
+    return results.map((response) => response.id);
+  }
+
+  private async crawl(paths: string[], options: UploadOptionsDto): Promise<string[]> {
+    const formatResponse = await getSupportedMediaTypes();
+    const crawlService = new CrawlService(formatResponse.image, formatResponse.video);
+
+    return crawlService.crawl({
+      pathsToCrawl: paths,
+      recursive: options.recursive,
+      exclusionPatterns: options.exclusionPatterns,
+      includeHidden: options.includeHidden,
+    });
+  }
+
+  private async uploadAsset(data: FormData): Promise<{ id: string }> {
+    const { baseUrl, headers } = defaults;
+
+    const response = await fetch(`${baseUrl}/asset/upload`, {
+      method: 'post',
+      redirect: 'error',
+      headers: headers as Record<string, string>,
+      body: data,
+    });
+    if (response.status !== 200 && response.status !== 201) {
+      throw new Error(await response.text());
+    }
+    return response.json();
+  }
+}
@@ -3,12 +3,12 @@ import { existsSync } from 'node:fs';
 import { mkdir, unlink } from 'node:fs/promises';
 import { BaseOptions, connect, getAuthFilePath, logError, withError, writeAuthFile } from 'src/utils';

-export const login = async (url: string, key: string, options: BaseOptions) => {
-  console.log(`Logging in to ${url}`);
+export const login = async (instanceUrl: string, apiKey: string, options: BaseOptions) => {
+  console.log(`Logging in to ${instanceUrl}`);

  const { configDirectory: configDir } = options;

-  await connect(url, key);
+  await connect(instanceUrl, apiKey);

  const [error, userInfo] = await withError(getMyUserInfo());
  if (error) {
@@ -27,7 +27,7 @@ export const login = async (url: string, key: string, options: BaseOptions) => {
    }
  }

-  await writeAuthFile(configDir, { url, key });
+  await writeAuthFile(configDir, { instanceUrl, apiKey });

  console.log(`Wrote auth info to ${getAuthFilePath(configDir)}`);
 };
@@ -1,24 +1,15 @@
-import { getAssetStatistics, getMyUserInfo, getServerVersion, getSupportedMediaTypes } from '@immich/sdk';
+import { getAssetStatistics, getServerVersion, getSupportedMediaTypes } from '@immich/sdk';
 import { BaseOptions, authenticate } from 'src/utils';

 export const serverInfo = async (options: BaseOptions) => {
-  const { url } = await authenticate(options);
+  await authenticate(options);

-  const [versionInfo, mediaTypes, stats, userInfo] = await Promise.all([
-    getServerVersion(),
-    getSupportedMediaTypes(),
-    getAssetStatistics({}),
-    getMyUserInfo(),
-  ]);
+  const versionInfo = await getServerVersion();
+  const mediaTypes = await getSupportedMediaTypes();
+  const stats = await getAssetStatistics({});

-  console.log(`Server Info (via ${userInfo.email})`);
-  console.log(`  Url: ${url}`);
-  console.log(`  Version: ${versionInfo.major}.${versionInfo.minor}.${versionInfo.patch}`);
-  console.log(`  Formats:`);
-  console.log(`    Images: ${mediaTypes.image.map((extension) => extension.replace('.', ''))}`);
-  console.log(`    Videos: ${mediaTypes.video.map((extension) => extension.replace('.', ''))}`);
-  console.log(`  Statistics:`);
-  console.log(`    Images: ${stats.images}`);
-  console.log(`    Videos: ${stats.videos}`);
-  console.log(`    Total: ${stats.total}`);
+  console.log(`Server Version: ${versionInfo.major}.${versionInfo.minor}.${versionInfo.patch}`);
+  console.log(`Image Types: ${mediaTypes.image.map((extension) => extension.replace('.', ''))}`);
+  console.log(`Video Types: ${mediaTypes.video.map((extension) => extension.replace('.', ''))}`);
+  console.log(`Statistics:\n  Images: ${stats.images}\n  Videos: ${stats.videos}\n  Total: ${stats.total}`);
 };
@@ -19,7 +19,7 @@ const program = new Command()
      .default(defaultConfigDirectory),
  )
  .addOption(new Option('-u, --url [url]', 'Immich server URL').env('IMMICH_INSTANCE_URL'))
-  .addOption(new Option('-k, --key [key]', 'Immich API key').env('IMMICH_API_KEY'));
+  .addOption(new Option('-k, --key [apiKey]', 'Immich API key').env('IMMICH_API_KEY'));

 program
  .command('login')
@@ -1,31 +1,14 @@
 import mockfs from 'mock-fs';
-import { CrawlOptions, crawl } from 'src/utils';
+import { CrawlOptions, CrawlService } from './crawl.service';

 interface Test {
  test: string;
-  options: Omit<CrawlOptions, 'extensions'>;
+  options: CrawlOptions;
  files: Record<string, boolean>;
 }

 const cwd = process.cwd();

-const extensions = [
-  '.jpg',
-  '.jpeg',
-  '.png',
-  '.heif',
-  '.heic',
-  '.tif',
-  '.nef',
-  '.webp',
-  '.tiff',
-  '.dng',
-  '.gif',
-  '.mov',
-  '.mp4',
-  '.webm',
-];
-
 const tests: Test[] = [
  {
    test: 'should return empty when crawling an empty path list',
@@ -268,7 +251,12 @@ const tests: Test[] = [
  },
 ];

-describe('crawl', () => {
+describe(CrawlService.name, () => {
+  const sut = new CrawlService(
+    ['.jpg', '.jpeg', '.png', '.heif', '.heic', '.tif', '.nef', '.webp', '.tiff', '.dng', '.gif'],
+    ['.mov', '.mp4', '.webm'],
+  );
+
  afterEach(() => {
    mockfs.restore();
  });
@@ -278,7 +266,7 @@ describe('crawl', () => {
      it(test, async () => {
        mockfs(Object.fromEntries(Object.keys(files).map((file) => [file, ''])));

-        const actual = await crawl({ ...options, extensions });
+        const actual = await sut.crawl(options);
        const expected = Object.entries(files)
          .filter((entry) => entry[1])
          .map(([file]) => file);
@@ -0,0 +1,70 @@
+import { glob } from 'glob';
+import * as fs from 'node:fs';
+
+export class CrawlOptions {
+  pathsToCrawl!: string[];
+  recursive? = false;
+  includeHidden? = false;
+  exclusionPatterns?: string[];
+}
+
+export class CrawlService {
+  private readonly extensions!: string[];
+
+  constructor(image: string[], video: string[]) {
+    this.extensions = [...image, ...video].map((extension) => extension.replace('.', ''));
+  }
+
+  async crawl(options: CrawlOptions): Promise<string[]> {
+    const { recursive, pathsToCrawl, exclusionPatterns, includeHidden } = options;
+
+    if (!pathsToCrawl) {
+      return [];
+    }
+
+    const patterns: string[] = [];
+    const crawledFiles: string[] = [];
+
+    for await (const currentPath of pathsToCrawl) {
+      try {
+        const stats = await fs.promises.stat(currentPath);
+        if (stats.isFile() || stats.isSymbolicLink()) {
+          crawledFiles.push(currentPath);
+        } else {
+          patterns.push(currentPath);
+        }
+      } catch (error: any) {
+        if (error.code === 'ENOENT') {
+          patterns.push(currentPath);
+        } else {
+          throw error;
+        }
+      }
+    }
+
+    let searchPattern: string;
+    if (patterns.length === 1) {
+      searchPattern = patterns[0];
+    } else if (patterns.length === 0) {
+      return crawledFiles;
+    } else {
+      searchPattern = '{' + patterns.join(',') + '}';
+    }
+
+    if (recursive) {
+      searchPattern = searchPattern + '/**/';
+    }
+
+    searchPattern = `${searchPattern}/*.{${this.extensions.join(',')}}`;
+
+    const globbedFiles = await glob(searchPattern, {
+      absolute: true,
+      nocase: true,
+      nodir: true,
+      dot: includeHidden,
+      ignore: exclusionPatterns,
+    });
+
+    return [...crawledFiles, ...globbedFiles].sort();
+  }
+}
@@ -1,61 +1,54 @@
 import { defaults, getMyUserInfo, isHttpError } from '@immich/sdk';
-import { glob } from 'glob';
-import { createHash } from 'node:crypto';
-import { createReadStream } from 'node:fs';
-import { readFile, stat, writeFile } from 'node:fs/promises';
+import { readFile, writeFile } from 'node:fs/promises';
 import { join } from 'node:path';
 import yaml from 'yaml';

 export interface BaseOptions {
  configDirectory: string;
-  key?: string;
-  url?: string;
+  apiKey?: string;
+  instanceUrl?: string;
 }

-export type AuthDto = { url: string; key: string };
-type OldAuthDto = { instanceUrl: string; apiKey: string };
+export interface AuthDto {
+  instanceUrl: string;
+  apiKey: string;
+}

-export const authenticate = async (options: BaseOptions): Promise<AuthDto> => {
-  const { configDirectory: configDir, url, key } = options;
+export const authenticate = async (options: BaseOptions): Promise<void> => {
+  const { configDirectory: configDir, instanceUrl, apiKey } = options;

  // provided in command
-  if (url && key) {
-    return connect(url, key);
+  if (instanceUrl && apiKey) {
+    await connect(instanceUrl, apiKey);
+    return;
  }

-  // fallback to auth file
+  // fallback to file
  const config = await readAuthFile(configDir);
-  const auth = await connect(config.url, config.key);
-  if (auth.url !== config.url) {
-    await writeAuthFile(configDir, auth);
-  }
-
-  return auth;
+  await connect(config.instanceUrl, config.apiKey);
 };

-export const connect = async (url: string, key: string) => {
-  const wellKnownUrl = new URL('.well-known/immich', url);
+export const connect = async (instanceUrl: string, apiKey: string): Promise<void> => {
+  const wellKnownUrl = new URL('.well-known/immich', instanceUrl);
  try {
    const wellKnown = await fetch(wellKnownUrl).then((response) => response.json());
-    const endpoint = new URL(wellKnown.api.endpoint, url).toString();
-    if (endpoint !== url) {
+    const endpoint = new URL(wellKnown.api.endpoint, instanceUrl).toString();
+    if (endpoint !== instanceUrl) {
      console.debug(`Discovered API at ${endpoint}`);
    }
-    url = endpoint;
+    instanceUrl = endpoint;
  } catch {
    // noop
  }

-  defaults.baseUrl = url;
-  defaults.headers = { 'x-api-key': key };
+  defaults.baseUrl = instanceUrl;
+  defaults.headers = { 'x-api-key': apiKey };

  const [error] = await withError(getMyUserInfo());
  if (isHttpError(error)) {
    logError(error, 'Failed to connect to server');
    process.exit(1);
  }
-
-  return { url, key };
 };

 export const logError = (error: unknown, message: string) => {
@@ -73,12 +66,7 @@ export const readAuthFile = async (dir: string) => {
  try {
    const data = await readFile(getAuthFilePath(dir));
    // TODO add class-transform/validation
-    const auth = yaml.parse(data.toString()) as AuthDto | OldAuthDto;
-    const { instanceUrl, apiKey } = auth as OldAuthDto;
-    if (instanceUrl && apiKey) {
-      return { url: instanceUrl, key: apiKey };
-    }
-    return auth as AuthDto;
+    return yaml.parse(data.toString()) as AuthDto;
  } catch (error: Error | any) {
    if (error.code === 'ENOENT' || error.code === 'ENOTDIR') {
      console.log('No auth file exists. Please login first.');
@@ -99,74 +87,3 @@ export const withError = async <T>(promise: Promise<T>): Promise<[Error, undefin
    return [error, undefined];
  }
 };
-
-export interface CrawlOptions {
-  pathsToCrawl: string[];
-  recursive?: boolean;
-  includeHidden?: boolean;
-  exclusionPatterns?: string[];
-  extensions: string[];
-}
-export const crawl = async (options: CrawlOptions): Promise<string[]> => {
-  const { extensions: extensionsWithPeriod, recursive, pathsToCrawl, exclusionPatterns, includeHidden } = options;
-  const extensions = extensionsWithPeriod.map((extension) => extension.replace('.', ''));
-
-  if (pathsToCrawl.length === 0) {
-    return [];
-  }
-
-  const patterns: string[] = [];
-  const crawledFiles: string[] = [];
-
-  for await (const currentPath of pathsToCrawl) {
-    try {
-      const stats = await stat(currentPath);
-      if (stats.isFile() || stats.isSymbolicLink()) {
-        crawledFiles.push(currentPath);
-      } else {
-        patterns.push(currentPath);
-      }
-    } catch (error: any) {
-      if (error.code === 'ENOENT') {
-        patterns.push(currentPath);
-      } else {
-        throw error;
-      }
-    }
-  }
-
-  let searchPattern: string;
-  if (patterns.length === 1) {
-    searchPattern = patterns[0];
-  } else if (patterns.length === 0) {
-    return crawledFiles;
-  } else {
-    searchPattern = '{' + patterns.join(',') + '}';
-  }
-
-  if (recursive) {
-    searchPattern = searchPattern + '/**/';
-  }
-
-  searchPattern = `${searchPattern}/*.{${extensions.join(',')}}`;
-
-  const globbedFiles = await glob(searchPattern, {
-    absolute: true,
-    nocase: true,
-    nodir: true,
-    dot: includeHidden,
-    ignore: exclusionPatterns,
-  });
-
-  return [...crawledFiles, ...globbedFiles].sort();
-};
-
-export const sha1 = (filepath: string) => {
-  const hash = createHash('sha1');
-  return new Promise<string>((resolve, reject) => {
-    const rs = createReadStream(filepath);
-    rs.on('error', reject);
-    rs.on('data', (chunk) => hash.update(chunk));
-    rs.on('end', () => resolve(hash.digest('hex')));
-  });
-};
@@ -2,6 +2,8 @@
 # - https://immich.app/docs/developer/setup
 # - https://immich.app/docs/developer/troubleshooting

+version: '3.8'
+
 name: immich-dev

 x-server-build: &server-common
@@ -97,7 +99,7 @@ services:

  redis:
    container_name: immich_redis
-    image: redis:6.2-alpine@sha256:3fcb624d83a9c478357f16dc173c58ded325ccc5fd2a4375f3916c04cc579f70
+    image: redis:6.2-alpine@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5

  database:
    container_name: immich_postgres
@@ -1,3 +1,5 @@
+version: '3.8'
+
 name: immich-prod

 x-server-build: &server-common
@@ -54,7 +56,7 @@ services:

  redis:
    container_name: immich_redis
-    image: redis:6.2-alpine@sha256:3fcb624d83a9c478357f16dc173c58ded325ccc5fd2a4375f3916c04cc579f70
+    image: redis:6.2-alpine@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5
    restart: always

  database:
@@ -76,7 +78,7 @@ services:
    container_name: immich_prometheus
    ports:
      - 9090:9090
-    image: prom/prometheus@sha256:5ccad477d0057e62a7cd1981ffcc43785ac10c5a35522dc207466ff7e7ec845f
+    image: prom/prometheus@sha256:bc1794e85c9e00293351b967efa267ce6af1c824ac875a9d0c7ac84700a8b53e
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
      - prometheus-data:/prometheus
@@ -88,7 +90,7 @@ services:
    command: ['./run.sh', '-disable-reporting']
    ports:
      - 3000:3000
-    image: grafana/grafana:10.4.1-ubuntu@sha256:65e0e7d0f0b001cb0478bce5093bff917677dc308dd27a0aa4b3ac38e4fd877c
+    image: grafana/grafana:10.4.0-ubuntu@sha256:c1f582b7cc4c1b9805d187b5600ce7879550a12ef6d29571da133c3d3fc67a9c
    volumes:
      - grafana-data:/var/lib/grafana

@@ -1,3 +1,5 @@
+version: '3.8'
+
 #
 # WARNING: Make sure to use the docker-compose.yml of the current release:
 #
@@ -10,8 +10,8 @@ Hello everyone, it is my pleasure to deliver the new release of Immich to you. T

 Some notable features are:

- OAuth integration
- LivePhoto support on iOS
+- [OAuth integration](#livephoto-ios-support-)
+- [LivePhoto support on iOS](#oauth-integration-)
 - User config system

 <!--truncate-->
@@ -288,11 +288,7 @@ Immich components are typically deployed using docker. To see logs for deployed
 ### How can I run Immich as a non-root user?

 You can change the user in the container by setting the `user` argument in `docker-compose.yml` for each service.
-You may need to add mount points or docker volumes for the following internal container paths:
-
- `immich-machine-learning:/.config`
- `immich-machine-learning:/.cache`
- `redis:/data`
+You may need to add an additional volume to `immich-microservices` that mounts internally to `/usr/src/app/.reverse-geocoding-dump`.

 The non-root user/group needs read/write access to the volume mounts, including `UPLOAD_LOCATION`.

@@ -20,7 +20,7 @@ The recommended way to backup and restore the Immich database is to use the `pg_
 <Tabs>
  <TabItem value="Linux system based Backup" label="Linux system based Backup" default>

-```bash title='Backup'
+```bash title='Bash'
 docker exec -t immich_postgres pg_dumpall -c -U postgres | gzip > "/path/to/backup/dump.sql.gz"
 ```

@@ -1,13 +1,9 @@
 # Jobs

-The `immich-server` responds to API requests for data and files for the web and mobile app. To do this quickly and reliably, it offloads most other work to `immich-microservices` in the form of _jobs_. Simply put, a job is a request to process data in the background. Jobs are picked up automatically by microservices containers.
+Several Immich functionalities are implemented as jobs, which run in the background. To view the status of a job navigate to the Administration Screen, and then the `Jobs` page.

-When a new asset is uploaded it kicks off a series of jobs, which include metadata extraction, thumbnail generation, machine learning tasks, and storage template migration, if enabled. To view the status of a job navigate to the Administration -> Jobs page.
-
-Additionally, some jobs run on a schedule, which is every night at midnight. This schedule, with the exception of [External Libraries](/docs/features/libraries) scanning, cannot be changed.
+![Admin jobs](./img/admin-jobs.png)

 :::info
 Storage Migration job can be run after changing the [Storage Template](/docs/administration/storage-template.mdx), in order to apply the change to the existing library.
 :::
-
-<img src={require('./img/admin-jobs.png').default} width="80%" title="Admin jobs" />
@@ -11,7 +11,7 @@ Unable to set `app.immich:/` as a valid redirect URI? See [Mobile Redirect URI](
 Immich supports 3rd party authentication via [OpenID Connect][oidc] (OIDC), an identity layer built on top of OAuth2. OIDC is supported by most identity providers, including:

 - [Authentik](https://goauthentik.io/integrations/sources/oauth/#openid-connect)
- [Authelia](https://www.authelia.com/configuration/identity-providers/openid-connect/clients/)
+- [Authelia](https://www.authelia.com/configuration/identity-providers/open-id-connect/)
 - [Okta](https://www.okta.com/openid-connect/)
 - [Google](https://developers.google.com/identity/openid-connect/openid-connect)

@@ -67,20 +67,14 @@ Once you have a new OAuth client application configured, Immich can be configure
 | Client Secret                                        | string  | (required)           | Required. Client Secret (previous step)                                             |
 | Scope                                                | string  | openid email profile | Full list of scopes to send with the request (space delimited)                      |
 | Signing Algorithm                                    | string  | RS256                | The algorithm used to sign the id token (examples: RS256, HS256)                    |
-| Storage Label Claim                                  | string  | preferred_username   | Claim mapping for the user's storage label**¹**                                     |
-| Storage Quota Claim                                  | string  | immich_quota         | Claim mapping for the user's storage**¹**                                           |
+| Storage Label Claim                                  | string  | preferred_username   | Claim mapping for the user's storage label                                          |
+| Storage Quota Claim                                  | string  | immich_quota         | Claim mapping for the user's storage                                                |
 | Default Storage Quota (GiB)                          | number  | 0                    | Default quota for user without storage quota claim (Enter 0 for unlimited quota)    |
 | Button Text                                          | string  | Login with OAuth     | Text for the OAuth button on the web                                                |
 | Auto Register                                        | boolean | true                 | When true, will automatically register a user the first time they sign in           |
 | [Auto Launch](#auto-launch)                          | boolean | false                | When true, will skip the login page and automatically start the OAuth login process |
 | [Mobile Redirect URI Override](#mobile-redirect-uri) | URL     | (empty)              | Http(s) alternative mobile redirect URI                                             |

-:::note Claim Options [1]
-
-Claim is only used on user creation and not synchronized after that.
-
-:::
-
 :::info
 The Issuer URL should look something like the following, and return a valid json document.

@@ -0,0 +1,32 @@
+# Password Login
+
+An overview of password login and related settings for Immich.
+
+## Enable/Disable
+
+Immich supports password login, which is enabled by default. The preferred way to disable it is via the [Administration Page](#administration-page), although it can also be changed via a [Server Command](#server-command) as well.
+
+### Administration Page
+
+To toggle the password login setting via the web, navigate to the "Administration", expand "Password Authentication", toggle the "Enabled" switch, and press "Save".
+
+![Password Login Settings](./img/password-login-settings.png)
+
+### Server Command
+
+There are two [Server Commands](/docs/administration/server-commands.md) for password login:
+
+1. `enable-password-login`
+2. `disable-password-login`
+
+See [Server Commands](/docs/administration/server-commands.md) for more details about how to run them.
+
+## Password Reset
+
+### Admin
+
+To reset the administrator password, use the `reset-admin-password` [Server Command](/docs/administration/server-commands.md).
+
+### User
+
+Immich does not currently support self-service password reset. However, the administration can reset passwords for other users. See [User Management: Password Reset](/docs/administration/user-management.mdx#password-reset) for more information about how to do this.
@@ -1,54 +0,0 @@
-# Preparing a pre-existing Postgres server
-
-While not officially recommended, it is possible to run Immich using a pre-existing Postgres server. To use this setup, you should have a baseline level of familiarity with Postgres and the Linux command line. If you do not have these, we recommend using the default setup with a dedicated Postgres container.
-
-By default, Immich expects superuser permission on the Postgres database and requires certain extensions to be installed. This guide outlines the steps required to prepare a pre-existing Postgres server to be used by Immich.
-
-:::tip
-Running with a pre-existing Postgres server can unlock powerful administrative features, including logical replication, data page checksums, and streaming write-ahead log backups using programs like pgBackRest or Barman.
-:::
-
-## Prerequisites
-
-You must install pgvecto.rs using their [instructions](https://docs.pgvecto.rs/getting-started/installation.html). After installation, add `shared_preload_libraries = 'vectors.so'` to your `postgresql.conf`. If you already have some `shared_preload_libraries` set, you can separate each extension with a comma. For example, `shared_preload_libraries = 'pg_stat_statements, vectors.so'`.
-
-:::note
-Make sure the installed version of pgvecto.rs is compatible with your version of Immich. For example, if your Immich version uses the dedicated database image `tensorchord/pgvecto-rs:pg14-v0.2.1`, you must install pgvecto.rs `>= 0.2.1, < 0.3.0`.
-:::
-
-## Specifying the connection URL
-
-You can connect to your pre-existing Postgres server by setting the `DB_URL` environment variable in the `.env` file.
-
-```
-DB_URL='postgresql://immichdbusername:immichdbpassword@postgreshost:postgresport/immichdatabasename'
-
-# require a SSL connection to Postgres
-# DB_URL='postgresql://immichdbusername:immichdbpassword@postgreshost:postgresport/immichdatabasename?sslmode=require'
-
-# require a SSL connection, but don't enforce checking the certificate name
-# DB_URL='postgresql://immichdbusername:immichdbpassword@postgreshost:postgresport/immichdatabasename?sslmode=require&sslmode=no-verify'
-```
-
-## Without superuser permissions
-
-### Initial installation
-
-Immich can run without superuser permissions by following the below instructions at the `psql` prompt to prepare the database.
-
-```sql title="Set up Postgres for Immich"
-CREATE DATABASE <immichdatabasename>;
-\c <immichdatabasename>
-BEGIN;
-ALTER DATABASE <immichdatabasename> OWNER TO <immichdbusername>;
-CREATE EXTENSION vectors;
-CREATE EXTENSION earthdistance CASCADE;
-ALTER DATABASE <immichdatabasename> SET search_path TO "$user", public, vectors;
-GRANT USAGE ON SCHEMA vectors TO <immichdbusername>;
-GRANT SELECT ON TABLE pg_vector_index_stat to <immichdbusername>;
-COMMIT;
-```
-
-### Updating pgvecto.rs
-
-When installing a new version of pgvecto.rs, you will need to manually update the extension by connecting to the Immich database and running `ALTER EXTENSION vectors UPDATE;`.
@@ -1,31 +0,0 @@
-# Repair Page
-
-The repair page is designed to give information to the system administrator about files that are not tracked, or offline paths.
-
-## Natural State
-
-In this situation, everything is in its place and there is no problem that the system administrator should be aware of.
-
-<img src={require('./img/repair-page.png').default} title="server statistic" />
-
-## Any Other Situation
-
-:::note RAM Usage
-Several users report a situation where the page fails to load. In order to solve this problem you should try to allocate more RAM to Immich, if the problem continues, you should stop using the reverse proxy while loading the page.
-:::
-
-In any other situation, there are 3 different options that can appear:
-
- MATCHES - These files are matched by their checksums.
-
- OFFLINE PATHS - These files are the result of manually deleting files in the upload library or a failed file move in the past (losing track of a file).
-
-:::tip
-To get rid of Offline paths you can follow this [guide](/docs/guides/remove-offline-files.md)
-:::
-
- UNTRACKED FILES - These files are not tracked by the application. They can be the result of failed moves, interrupted uploads, or left behind due to a bug.
-
-In addition, you can download the information from a page, mark everything (in order to check hashing) and correct the problem if a match is found in the hashing.
-
-<img src={require('./img/repair-page-1.png').default} title="server statistic" />
@@ -1,41 +1,29 @@
 # Reverse Proxy

-Users can deploy a custom reverse proxy that forwards requests to Immich. This way, the reverse proxy can handle TLS termination, load balancing, or other advanced features. All reverse proxies between Immich and the user must forward all headers and set the `Host`, `X-Real-IP`, `X-Forwarded-Proto` and `X-Forwarded-For` headers to their appropriate values. Additionally, your reverse proxy should allow for big enough uploads. By following these practices, you ensure that all custom reverse proxies are fully compatible with Immich.
-
-:::note
-The Repair page can take a long time to load. To avoid server timeouts or errors, we recommend specifying a timeout of at least 10 minutes on your proxy server.
-:::
+Users can deploy a custom reverse proxy that forwards requests to Immich. This way, the reverse proxy can handle TLS termination, load balancing, or other advanced features. All reverse proxies between Immich and the user must forward all headers and set the `Host`, `X-Forwarded-Host`, `X-Forwarded-Proto` and `X-Forwarded-For` headers to their appropriate values. Additionally, your reverse proxy should allow for big enough uploads. By following these practices, you ensure that all custom reverse proxies are fully compatible with Immich.

 ### Nginx example config

-Below is an example config for nginx. Make sure to set `public_url` to the front-facing URL of your instance, and `backend_url` to the path of the Immich server.
+Below is an example config for nginx. Make sure to include `client_max_body_size 50000M;` also in a `http` block in `/etc/nginx/nginx.conf`.

 ```nginx
 server {
-    server_name <public_url>;
+    server_name <snip>

-    # allow large file uploads
    client_max_body_size 50000M;

-    # Set headers
-    proxy_set_header Host              $http_host;
-    proxy_set_header X-Real-IP         $remote_addr;
-    proxy_set_header X-Forwarded-For   $proxy_add_x_forwarded_for;
-    proxy_set_header X-Forwarded-Proto $scheme;
-
-    # enable websockets: http://nginx.org/en/docs/http/websocket.html
-    proxy_http_version 1.1;
-    proxy_set_header   Upgrade    $http_upgrade;
-    proxy_set_header   Connection "upgrade";
-    proxy_redirect     off;
-
-    # set timeout
-    proxy_read_timeout 600s;
-    proxy_send_timeout 600s;
-    send_timeout       600s;
-
    location / {
-        proxy_pass http://<backend_url>:2283;
+        proxy_pass http://<snip>:2283;
+        proxy_set_header Host              $http_host;
+        proxy_set_header X-Real-IP         $remote_addr;
+        proxy_set_header X-Forwarded-For   $proxy_add_x_forwarded_for;
+        proxy_set_header X-Forwarded-Proto $scheme;
+
+        # http://nginx.org/en/docs/http/websocket.html
+        proxy_http_version 1.1;
+        proxy_set_header   Upgrade    $http_upgrade;
+        proxy_set_header   Connection "upgrade";
+        proxy_redirect off;
    }
 }
 ```
@@ -54,13 +42,15 @@ immich.example.org {

 Below is an example config for Apache2 site configuration.

-```ApacheConf
+```
 <VirtualHost *:80>
   ServerName <snip>
   ProxyRequests Off
-   # set timeout in seconds
   ProxyPass / http://127.0.0.1:2283/ timeout=600 upgrade=websocket
   ProxyPassReverse / http://127.0.0.1:2283/
   ProxyPreserveHost On
+
 </VirtualHost>
 ```
+
+**timeout:** is measured in seconds, and it is particularly useful when long operations are triggered (i.e. Repair), so the server doesn't return an error.
@@ -1,13 +0,0 @@
-# Server Stats
-
-Server statistics to show the total number of videos, photos, and usage per user.
-
-:::info
-If a storage quota has been defined for the user, the usage number will be displayed as a percentage of the total storage quota allocated to him.
-:::
-
-:::info External library
-External library is not included in the storage quota.
-:::
-
-<img src={require('./img/server-stats.png').default} title="server statistic" />
@@ -1,173 +0,0 @@
-# System Settings
-
-On the system settings page, the administrator can manage global settings for the Immich instance.
-
-:::note
-Viewing and modifying the system settings is restricted to the Administrator.
-:::
-
-:::tip
-You can always return to the default settings by clicking the `Reset to default` button.
-:::
-
-## Job Settings
-
-Using these settings, you can determine the amount of work that will run concurrently for each task in microservices. Some tasks can be set to higher values on computers with powerful hardware and storage with good I/O capabilities.
-
-With higher concurrency, the host will work on more assets in parallel,
-this advice improves throughput, not latency, for example, it will make Smart Search jobs process more quickly, but it won't make searching faster.
-
-It is important to remember that jobs like Smart Search, Face Detection, Facial Recognition, and Transcode Videos require a **lot** of processing power and therefore do not exaggerate the amount of jobs because you're probably thoroughly overloading the server.
-
-:::info Facial Recognition Concurrency
-The Facial Recognition Concurrency value cannot be changed because
-[DBSCAN](https://www.youtube.com/watch?v=RDZUdRSDOok) is traditionally sequential, but there are parallel implementations of it out there. Our implementation isn't parallel.
-:::
-
-## External Library
-
-### Library watching (EXPERIMENTAL)
-
-External libraries can automatically import changed files without a full rescan. It will import the file whenever the operating system reports a file change. If your photos are mounted over the network, this does not work.
-
-### Periodic Scanning
-
-You can define a custom interval for the trigger external library rescan under Administration -> Settings -> Library.  
-You can set the scanning interval using the preset or cron format. For more information please refer to e.g. [Crontab Guru](https://crontab.guru/).
-
-## Logging
-
-By default logs are set to record at the log level, the network administrator can choose a deeper or lower level of logs according to his decision or according to the needs required by the Immich support team.
-
-Here you can [learn about the different error levels](https://sematext.com/blog/logging-levels/).
-
-## Machine Learning Settings
-
-Through this setting, you can manage all the settings related to machine learning in Immich, from the setting of remote machine learning to the model and its parameters
-You can choose to disable a certain type of machine learning, for example smart search or facial recognition.
-
-### Smart Search
-
-The smart search settings are designed to allow the search tool to be used using [CLIP](https://openai.com/research/clip) models that [can be changed](/docs/FAQ#can-i-use-a-custom-clip-model), different models will necessarily give better results but may consume more processing power, when changing a model it is mandatory to re-run the
-Smart Search job on all images to fully apply the change.
-
-:::info Internet connection
-Changing models requires a connection to the Internet to download the model.
-After downloading, there is no need for Immich to connect to the network
-Unless version checking has been enabled in the settings.
-:::
-
-### Facial Recognition
-
-Under these settings, you can change the facial recognition settings
-Editable settings:
-
- **Facial Recognition Model -** Models are listed in descending order of size. Larger models are slower and use more memory, but produce better results. Note that you must re-run the Face Detection job for all images upon changing a model.
- **Min Detection Score -** Minimum confidence score for a face to be detected from 0-1. Lower values will detect more faces but may result in false positives.
- **Max Recognition Distance -** Maximum distance between two faces to be considered the same person, ranging from 0-2. Lowering this can prevent labeling two people as the same person, while raising it can prevent labeling the same person as two different people. Note that it is easier to merge two people than to split one person in two, so err on the side of a lower threshold when possible.
- **Min Recognized Faces -** The minimum number of recognized faces for a person to be created (AKA: Core face). Increasing this makes Facial Recognition more precise at the cost of increasing the chance that a face is not assigned to a person.
-
-:::info
-When changing the values in Min Detection Score, Max Recognition Distance, and Min Recognized Faces.
-You will have to restart **only** the job FACIAL RECOGNITION - ALL.
-
-If you replace the Facial Recognition Model, you will have to run the job FACE DETECTION - ALL.
-:::
-
-:::tip identical twins
-If you have twins, you might want to lower the Max Recognition Distance value, decreasing this a **bit** can make it distinguish between them.
-:::
-
-## Map & GPS Settings
-
-### Map Settings
-
-In these settings, you can change the appearance of the map in night and day modes according to your personal preference and according to the supported options.
-The map can be adjusted via [OpenMapTiles](https://openmaptiles.org/styles/) for example.
-
-### Reverse Geocoding Settings
-
-Immich supports [Reverse Geocoding](/docs/features/reverse-geocoding) using data from the [GeoNames](https://www.geonames.org/) geographical database.
-
-## OAuth Authentication
-
-Immich supports OAuth Authentication. Read more about this feature and its configuration [here](/docs/administration/oauth).
-
-## Password Authentication
-
-The administrator can choose to disable login with username and password for the entire instance. This means that **no one**, including the system administrator, will be able to log using this method. If [OAuth Authentication](/docs/administration/oauth) is also disabled, no users will be able to login using **any** method. Changing this setting does not affect existing sessions, just new login attempts.
-
-:::tip
-You can always use the [Server CLI](/docs/administration/server-commands) to re-enable password login.
-:::
-
-## Server Settings
-
-### External Domain
-
-When set, will override the domain name used when viewing and copying a shared link.
-
-### Welcome Message
-
-The administrator can set a custom message on the login screen (the message will be displayed to all users).
-
-## Storage Template
-
-Immich supports a custom [Storage Template](/docs/administration/storage-template). Learn more about this feature and its configuration [here](/docs/administration/storage-template).
-
-## Theme Settings
-
-You can write custom CSS that will get loaded in the web application for all users. This enables administrators to change fonts, colors, and other styles.
-
-For example:
-
-```css title='Custom CSS'
-p {
-  color: green;
-}
-```
-
-## Thumbnail Settings
-
-By default Immich creates 3 thumbnails for each asset,
-Blurred (thumbhash) , Small (webp) , and Large (jpeg), using these settings you can change the quality for the thumbnail files that are created.
-
-**Small thumbnail resolution**  
-Used when viewing groups of photos (main timeline, album view, etc.). Higher resolutions can preserve more detail but take longer to encode, have larger file sizes, and can reduce app responsiveness.
-
-**Large thumbnail resolution**  
-Used when viewing a single photo and for machine learning. Higher resolutions can preserve more detail but take longer to encode, have larger file sizes, and can reduce app responsiveness.
-
-**Quality**  
-Thumbnail quality from 1-100. Higher is better for quality but produces larger files.
-
-**Prefer wide gamut**  
-Use display p3 for thumbnails. This better preserves the vibrance of images with wide color spaces, but images may appear differently on old devices with an old browser version. Srgb images are kept as srgb to avoid color shifts.
-
-:::tip
-The default resolution for Large thumbnails can be lowered from 1440p (default) to 1080p or 720p to save storage space.
-:::
-
-## Trash Settings
-
-In the system administrator's option to set a trash for deleted files, these files will remain in the trash until the deletion date 30 days (default) or as defined by the system administrator.
-
-The trash can be disabled, however this is not recommended as future files that are deleted will be permanently deleted.
-
-:::tip Keyboard shortcut for permanently deletion
-You can select assets and press Ctrl + Del from the timeline for quick permanent deletion without the trash option.
-:::
-
-## User Settings
-
-### Delete delay
-
-The system administrator can choose to delete users through the administration panel, the system administrator can delete users immediately or alternatively delay the deletion for users (7 days by default) this action permanently delete a user's account and assets. The user deletion job runs at midnight to check for users that are ready for deletion. Changes to this setting will be evaluated at the next execution.
-
-## Version Check
-
-When this option is enabled the `immich-server` will periodically make requests to GitHub to check for new releases.
-
-## Video Transcoding Settings
-
-The system administrator can define parameters according to which video files will be converted to different formats (depending on the settings). The settings can be changed in depth, to learn more about the terminology used here, refer to FFmpeg documentation for [H.264](https://trac.ffmpeg.org/wiki/Encode/H.264) codec, [HEVC](https://trac.ffmpeg.org/wiki/Encode/H.265) codec and [VP9](https://trac.ffmpeg.org/wiki/Encode/VP9) codec.
@@ -13,57 +13,12 @@ Immich supports multiple users, each with their own library.

 <UserCreate />

-## Set Storage Quota For User
+## Delete a User

-Admin can specify the storage quota for the user as the instance's admin; once the limit is reached, the user won't be able to upload to the instance anymore.
-
-In order to select a storage quota, click on the pencil icon and enter the storage quota in GiB. You can choose an unlimited quota using the value 0 (default).
-
-:::tip
-The system administrator can see the usage quota percentage of all users in Server Stats page.
-:::
-
-:::info
-External libraries don't take up space from the storage quota.
-:::
-
-<img src={require('./img/user-quota-size.png').default} width="40%" title="Set Quota Size" />
-
-## Set Storage Label For User
-
-The admin can add a custom label for each user, so instead of `upload/{userId}/your-template` it will be `upload/{custom_user_label}/your-template`.  
-To apply a storage template, go to the Administration page -> click on the pencil button next to the user.
-:::note
-To apply the Storage Label to previously uploaded assets, run the Storage Migration Job.
-:::
-
-<img src={require('./img/user-storage-label.png').default} width="40%" title="Delete User" />
+If you need to remove a user from Immich, head to "Administration", where users can be scheduled for deletion. The user account will immediately become disabled and their library and all associated data will be removed after 7 days.

 ## Password Reset

-To reset a user's password, click the pencil icon to edit a user, then click "Reset Password". The user's password will be reset to random password and they have to change it next time the sign in.
+To reset a user's password, click the pencil icon to edit a user, then click "Reset Password". The user's password will be reset to "password" and they have to change it next time the sign in.

-<img src={require('./img/user-management-update.png').default} width="40%" title="Reset Password" />
-
-## Delete a User
-
-If you need to remove a user from Immich, head to "Administration", where users can be scheduled for deletion. The user account will immediately become disabled and their library and all associated data will be removed after 7 days by default.
-
-<img src={require('./img/delete-user.webp').default} width="40%" title="Delete User" />
-
-### Delete Delay
-
-You can customize the time of the deletion of the users from the Administration -> Settings -> User Settings.
-:::info user deletion job
-The user deletion job runs at midnight to check for users that are ready for deletion. Changes to this setting will be evaluated at the next execution.
-:::
-
-<img src={require('./img/customize-delete-user.png').default} width="80%" title="Customize Delete User" />
-
-### Immediately Remove User
-
-You can choose to delete a user immediately by checking the box
-`Queue user and assets for immediate deletion` in the deletion process, this will immediately remove the user and all assets.
-This cannot be undone and the files cannot be recovered.
-
-<img src={require('./img/immediately-remove-user.png').default} width="40%" title="Customize Delete User" />
+![Reset Password](./img/user-management-update.png)
@@ -1,14 +1,14 @@
 # Database Migrations

-After making any changes in the `server/src/entities`, a database migration need to run in order to register the changes in the database. Follow the steps below to create a new migration.
+After making any changes in the `server/src/infra/entities`, a database migration need to run in order to register the changes in the database. Follow the steps below to create a new migration.

 1. Run the command

 ```bash
-npm run typeorm:migrations:generate <migration-name>
+npm run typeorm:migrations:generate ./src/infra/<migration-name>
 ```

 2. Check if the migration file makes sense.
-3. Move the migration file to folder `./server/src/migrations` in your code editor.
+3. Move the migration file to folder `./server/src/infra/migrations` in your code editor.

 The server will automatically detect `*.ts` file changes and restart. Part of the server start-up process includes running any new migrations, so it will be applied immediately.
@@ -1,6 +1,6 @@
 # The Immich CLI

-Immich has a command line interface (CLI) that allows you to perform certain actions from the command line.
+Immich has a CLI that allows you to perform certain actions from the command line. This CLI replaces the [legacy CLI](https://github.com/immich-app/CLI) that was previously available. The CLI is hosted in the [cli folder of the the main Immich github repository](https://github.com/immich-app/immich/tree/main/cli).

 ## Features

@@ -54,19 +54,16 @@ Usage: immich [options] [command]
 Command line interface for Immich

 Options:
-  -V, --version                       output the version number
-  -d, --config-directory <directory>  Configuration directory where auth.yml will be stored (default: "~/.config/immich/", env:
-                                      IMMICH_CONFIG_DIR)
-  -u, --url [url]                     Immich server URL (env: IMMICH_INSTANCE_URL)
-  -k, --key [key]                     Immich API key (env: IMMICH_API_KEY)
-  -h, --help                          display help for command
+  -V, --version                     output the version number
+  -d, --config                      Configuration directory (env: IMMICH_CONFIG_DIR)
+  -h, --help                        display help for command

 Commands:
-  login|login-key <url> <key>         Login using an API key
-  logout                              Remove stored credentials
-  server-info                         Display server information
-  upload [options] [paths...]         Upload assets
-  help [command]                      display help for command
+  upload [options] [paths...]       Upload assets
+  server-info                       Display server information
+  login-key [instanceUrl] [apiKey]  Login using an API key
+  logout                            Remove stored credentials
+  help [command]                    display help for command
 ```

 ## Commands
@@ -74,24 +71,23 @@ Commands:
 The upload command supports the following options:

 ```
-Usage: immich upload [paths...] [options]
+Usage: immich upload [options] [paths...]

 Upload assets

 Arguments:
-  paths                       One or more paths to assets to be uploaded
+  paths                    One or more paths to assets to be uploaded

 Options:
-  -r, --recursive             Recursive (default: false, env: IMMICH_RECURSIVE)
-  -i, --ignore [paths...]     Paths to ignore (default: [], env: IMMICH_IGNORE_PATHS)
-  -h, --skip-hash             Don't hash files before upload (default: false, env: IMMICH_SKIP_HASH)
-  -H, --include-hidden        Include hidden folders (default: false, env: IMMICH_INCLUDE_HIDDEN)
-  -a, --album                 Automatically create albums based on folder name (default: false, env: IMMICH_AUTO_CREATE_ALBUM)
-  -A, --album-name <name>     Add all assets to specified album (env: IMMICH_ALBUM_NAME)
-  -n, --dry-run               Don't perform any actions, just show what will be done (default: false, env: IMMICH_DRY_RUN)
-  -c, --concurrency <number>  Number of assets to upload at the same time (default: 4, env: IMMICH_UPLOAD_CONCURRENCY)
-  --delete                    Delete local assets after upload (env: IMMICH_DELETE_ASSETS)
-  --help                      display help for command
+  -r, --recursive          Recursive (default: false, env: IMMICH_RECURSIVE)
+  -i, --ignore [paths...]  Paths to ignore (env: IMMICH_IGNORE_PATHS)
+  -h, --skip-hash          Don't hash files before upload (default: false, env: IMMICH_SKIP_HASH)
+  -H, --include-hidden     Include hidden folders (default: false, env: IMMICH_INCLUDE_HIDDEN)
+  -a, --album              Automatically create albums based on folder name (default: false, env: IMMICH_AUTO_CREATE_ALBUM)
+  -A, --album-name <name>  Add all assets to specified album (env: IMMICH_ALBUM_NAME)
+  -n, --dry-run            Don't perform any actions, just show what will be done (default: false, env: IMMICH_DRY_RUN)
+  --delete                 Delete local assets after upload (env: IMMICH_DELETE_ASSETS)
+  --help                   display help for command
 ```

 Note that the above options can read from environment variables as well.
@@ -101,13 +97,13 @@ Note that the above options can read from environment variables as well.
 You begin by authenticating to your Immich server.

 ```bash
-immich login [url] [key]
+immich login-key [instanceUrl] [apiKey]
 ```

 For instance,

 ```bash
-immich login http://192.168.1.216:2283/api HFEJ38DNSDUEG
+immich login-key http://192.168.1.216:2283/api HFEJ38DNSDUEG
 ```

 This will store your credentials in a `auth.yml` file in the configuration directory which defaults to `~/.config/`. The directory can be set with the `-d` option or the environment variable `IMMICH_CONFIG_DIR`. Please keep the file secure, either by performing the logout command after you are done, or deleting it manually.
@@ -1,113 +0,0 @@
-# Monitoring
-
-## Overview
-
-Immich provides a variety of performance metrics to allow for local monitoring and insights. This integration is primarily in the form of Prometheus metrics. However, exporting traces is also possible due to the use of OpenTelemetry instrumentation.
-
-:::note
-This is an opt-in feature intended for you to monitor immich's performance. This data isn't sent anywhere beyond what you've configured.
-:::
-
-## Prometheus
-
-Prometheus is a tool that collects metrics from a number of sources you configure. It operates in a "pull" strategy - that is, it periodically requests metrics from each defined source. This means that the source doesn't send anything until it's requested. It also means that the source -- immich, in this case -- has to expose an endpoint for Prometheus to target when it requests metrics.
-
-### Metrics
-
-These metrics come in a variety of forms:
-
- Counters, which can only increase. Example: the number of times an endpoint has been called.
- Gauges, which can increase or decrease within a certain range. Example: CPU utilization.
- Histograms, where each observation is assigned to a certain number of "buckets". Example: response time, where each bucket is a number of milliseconds. This one is a bit more complicated.
-  - Buckets in this case are _cumulative_; that is, an observation is placed not only into the smallest bucket that contains it, but also to all buckets larger than this. For example, if a histogram has three buckets for 1ms, 5ms and 10ms, an observation of 3ms will be bucketed into both 5ms and 10ms.
-
-The metrics in immich are grouped into API (endpoint calls and response times), host (memory and CPU utilization), and IO (internal database queries, image processing, and so on). Each group of metrics can be enabled or disabled independently.
-
-### Configuration
-
-Immich will not expose an endpoint for metrics by default. To enable this endpoint, you can add the `IMMICH_METRICS=true` environmental variable to your `.env` file. Note that only the server and microservices containers currently use this variable.
-
-:::note
-`IMMICH_METRICS` is equivalent to enabling the following three environmental variables: `IMMICH_API_METRICS`, `IMMICH_HOST_METRICS`, and `IMMICH_IO_METRICS`. If you would like to only expose certain kinds of metrics, you can set only those environmental variables to `true`. Explicitly setting the environmental variable for a metric group overrides `IMMICH_METRICS` for that group.
-:::
-
-The next step is to configure a new or existing Prometheus instance to scrape this endpoint. The following steps assume that you do not have an existing Prometheus instance, but the steps will be similar either way.
-
-You can start by defining a Prometheus service in the Compose file:
-
-```yaml
-immich-prometheus:
-  container_name: immich_prometheus
-  ports:
-    # this exposes the default port for Prometheus so you can interact with it
-    - 9090:9090
-  image: prom/prometheus
-  volumes:
-    # the Prometheus configuration file - a barebones one is provided to get started
-    - ./prometheus.yml:/etc/prometheus/prometheus.yml
-    # a named volume defined in the bottom of the Compose file; it can also be a mounted folder
-    - prometheus-data:/prometheus
-```
-
-You will also need to add `prometheus-data` to the list of volumes in the bottom of the Compose file:
-
-```yaml
-volumes:
-  model-cache:
-  prometheus-data:
-```
-
-The last piece is the [configuration file][prom-file]. This file defines (among other things) the sources Prometheus should target. Download it and place it in the same folder as the Compose file.
-
-:::tip
-The provided file is just a starting point. There are a ton of ways to configure Prometheus, so feel free to experiment!
-:::
-
-After bringing down the containers with `docker compose down` and back up with `docker compose up -d`, a Prometheus instance will now collect metrics from the immich server and microservices containers. Note that we didn't need to expose any new ports for these containers - the communication is handled in the internal Docker network.
-
-:::note
-To see exactly what metrics are made available, you can additionally add `8081:8081` to the server container's ports and `8082:8081` to the microservices container's ports. Visiting the `/metrics` endpoint for these services will show the same raw data that Prometheus collects.
-:::
-
-### Usage
-
-So after setting up Prometheus, how do you actually view the metrics? The simplest way is to use Prometheus directly. Visiting Prometheus will show you a web UI where you can search for and visualize metrics. You can also view the status of your data sources and configure settings, but this is beyond the scope of this guide.
-
-## Grafana
-
-For a dedicated tool with nice presentation, you can use Grafana instead. This connects to Prometheus (and possibly other sources) for sophisticated data visualization.
-
-Setting up Grafana is similar to Prometheus. You can add a service for it:
-
-```yaml
-immich-grafana:
-  container_name: immich_grafana
-  command: ['./run.sh', '-disable-reporting'] # this is to disable Grafana's telemetry
-  ports:
-    - 3000:3000
-  image: grafana/grafana
-  volumes:
-    # stores your pretty dashboards and panels
-    - grafana-data:/var/lib/grafana
-```
-
-And add another volume for it:
-
-```yaml
-volumes:
-  model-cache:
-  prometheus-data:
-  grafana-data:
-```
-
-After bringing down the services and back up again, you can now visit Grafana to view your metrics. On the first login, enter `admin` for both username and password and update your password. You can then go to the settings and add a data source with `http://immich-prometheus:9090` to point Grafana to your Prometheus instance.
-
-### Usage
-
-You can make your first dashboard to get started. Don't forget to save it frequently, or you'll lose all your progress!
-
-You can then make a new panel, specifying Prometheus as the data source for it.
-
-- TODO: add images and more details here
-
-[prom-file]: https://github.com/immich-app/immich/releases/latest/download/prometheus.yml
@@ -6,7 +6,7 @@ Immich can ingest XMP sidecars on file upload (via the CLI) as well as detect ne

 XMP sidecars are external XML files that contain metadata related to media files. Many applications read and write these files either exclusively or in addition to the metadata written to image files. They can be a powerful tool for editing and storing metadata of a media file without modifying the media file itself. When Immich receives or detects an XMP sidecar for a media file, it will attempt to extract the metadata from both the sidecar as well as the media file. It will prioritize the metadata for fields in the sidecar but will fall back and use the metadata in the media file if necessary.

-When importing files via the CLI bulk uploader or parsing photo metadata for external libraries, Immich will automatically detect XMP sidecar files as files that exist next to the original media file. Immich will look files that have the same name as the photo, but with the `.xmp` file extension. The same name can either include the photo's file extension or without the photo's file extension. For example, for a photo named `PXL_20230401_203352928.MP.jpg`, Immich will look for an XMP file named either `PXL_20230401_203352928.MP.jpg.xmp` or `PXL_20230401_203352928.MP.xmp`. If both `PXL_20230401_203352928.MP.jpg.xmp` and `PXL_20230401_203352928.MP.xmp` are present, Immich will prefer `PXL_20230401_203352928.MP.jpg.xmp`.
+When importing files via the CLI bulk uploader, Immich will automatically detect XMP sidecar files as files that exist next to the original media file and have the exact same name with an additional `.xmp` file extension (i.e., `PXL_20230401_203352928.MP.jpg` and `PXL_20230401_203352928.MP.jpg.xmp`).

 There are 2 administrator jobs associated with sidecar files: `SYNC` and `DISCOVER`. The sync job will re-scan all media with existing sidecar files and queue them for a metadata refresh. This is a great use case when third-party applications are used to modify the metadata of media. The discover job will attempt to scan the filesystem for new sidecar files for all media that does not currently have a sidecar file associated with it.

@@ -56,4 +56,4 @@ A remote reverse proxy like [Cloudflare](https://www.cloudflare.com/learning/cdn
 ### Cons

 - Complex configuration
- Depending on your configuration, both the Immich web interface and API may be exposed to the internet. Immich is under very active development and the existence of severe security vulnerabilities cannot be ruled out.
+- Depending on your configuration, both the Immich web interface and API may be exposed to the internet. Immich is under very active developement and the existence of severe security vulnerabilities cannot be ruled out.
@@ -16,12 +16,7 @@ version: '3.8'
 services:
  immich-machine-learning:
    container_name: immich_machine_learning
-    # For hardware acceleration, add one of -[armnn, cuda, 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
    volumes:
      - model-cache:/cache
    restart: always
@@ -9,8 +9,8 @@ The database is saved to your Immich upload folder in the `database-backup` subd
 ### Prerequisites

 - Borg needs to be installed on your server as well as the remote machine. You can find instructions to install Borg [here](https://borgbackup.readthedocs.io/en/latest/installation.html).
- (Optional) To run this sript as a non-root user, you should [add your username to the docker group](https://docs.docker.com/engine/install/linux-postinstall/).
- To run this script non-interactively, set up [passwordless ssh](https://www.redhat.com/sysadmin/passwordless-ssh) to your remote machine from your server. If you skipped the previous step, make sure this step is done from your root account.
+- To run this sript as a non-root user, you should [add your username to the docker group](https://docs.docker.com/engine/install/linux-postinstall/).
+- To run this script non-interactively, set up [passwordless ssh](https://www.redhat.com/sysadmin/passwordless-ssh) to your remote machine from your server.

 To initialize the borg repository, run the following commands once.

@@ -19,13 +19,16 @@ UPLOAD_LOCATION="/path/to/immich/directory"       # Immich database location, as
 BACKUP_PATH="/path/to/local/backup/directory"

 mkdir "$UPLOAD_LOCATION/database-backup"
+mkdir "$BACKUP_PATH/immich-borg"
+
 borg init --encryption=none "$BACKUP_PATH/immich-borg"

 ## Remote set up
 REMOTE_HOST="remote_host@IP"
 REMOTE_BACKUP_PATH="/path/to/remote/backup/directory"

-borg init --encryption=none "$REMOTE_HOST:$REMOTE_BACKUP_PATH/immich-borg"
+ssh "$REMOTE_HOST" "mkdir \"$REMOTE_BACKUP_PATH\"/immich-borg"
+ssh "$REMOTE_HOST" "borg init --encryption=none \"$REMOTE_BACKUP_PATH\"/immich-borg"
 ```

 Edit the following script as necessary and add it to your crontab. Note that this script assumes there are no `:`, `@`, or `"` characters in your paths. If these characters exist, you will need to escape and/or rename the paths.
@@ -21,7 +21,7 @@ cd ./immich-app
 Download [`docker-compose.yml`][compose-file] and [`example.env`][env-file], either by running the following commands:

 ```bash title="Get docker-compose.yml file"
-wget -O docker-compose.yml https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml
+wget https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml
 ```

 ```bash title="Get .env file"
@@ -29,11 +29,11 @@ wget -O .env https://github.com/immich-app/immich/releases/latest/download/examp
 ```

 ```bash title="(Optional) Get hwaccel.transcoding.yml file"
-wget -O hwaccel.transcoding.yml https://github.com/immich-app/immich/releases/latest/download/hwaccel.transcoding.yml
+wget https://github.com/immich-app/immich/releases/latest/download/hwaccel.transcoding.yml
 ```

 ```bash title="(Optional) Get hwaccel.ml.yml file"
-wget -O hwaccel.ml.yml https://github.com/immich-app/immich/releases/latest/download/hwaccel.ml.yml
+wget https://github.com/immich-app/immich/releases/latest/download/hwaccel.ml.yml
 ```

 or by downloading from your browser and moving the files to the directory that you created.
@@ -36,14 +36,16 @@ These environment variables are used by the `docker-compose.yml` file and do **N
 | `NODE_ENV`                      | Environment (production, development)        |     `production`     | server, microservices, machine learning, web |
 | `LOG_LEVEL`                     | Log Level (verbose, debug, log, warn, error) |        `log`         | server, microservices                        |
 | `IMMICH_MEDIA_LOCATION`         | Media Location                               |      `./upload`      | server, microservices                        |
-| `IMMICH_CONFIG_FILE`            | Path to config file                          |                      | server, microservices                        |
+| `IMMICH_CONFIG_FILE`            | Path to config file                          |                      | server                                       |
 | `IMMICH_WEB_ROOT`               | Path of root index.html                      |  `/usr/src/app/www`  | server                                       |
 | `IMMICH_REVERSE_GEOCODING_ROOT` | Path of reverse geocoding dump directory     | `/usr/src/resources` | microservices                                |

 :::tip
-`TZ` should be set to a `TZ identifier` from [this list](https://en.wikipedia.org/wiki/List_of_tz_database_time_zones#List). For example, `TZ="Etc/UTC"`.

-`TZ` is only used by `exiftool`, which is present in the microservices container, as a fallback in case the timezone cannot be determined from the image metadata.
+`TZ` is only used by the `exiftool` as a fallback in case the timezone cannot be determined from the image metadata.
+
+`exiftool` is only present in the microservices container.
+
 :::

 ## Ports
@@ -1,7 +1,7 @@
 Immich allows the admin user to set the uploaded filename pattern. Both at the directory and filename level.

 :::note new version
-On new machines running version 1.92.0 storage template engine is off by default, for [more info](https://github.com/immich-app/immich/releases/tag/v1.92.0#:~:text=the%20partner%E2%80%99s%20assets.-,Hardening%20storage%20template,-We%20have%20further).
+On new machines running version 1.92.0 storage template engine is off by default, for [more info](https://github.com/immich-app/immich/releases#:~:text=the%20partner%E2%80%99s%20assets.-,Hardening%20storage%20template,-We%20have%20further).
 :::

 :::tip
@@ -4264,9 +4264,9 @@
      }
    },
    "node_modules/autoprefixer": {
-      "version": "10.4.19",
-      "resolved": "https://registry.npmjs.org/autoprefixer/-/autoprefixer-10.4.19.tgz",
-      "integrity": "sha512-BaENR2+zBZ8xXhM4pUaKUxlVdxZ0EZhjvbopwnXmxRUfqDmwSpC2lAi/QXvx7NRdPCo1WKEcEF6mV64si1z4Ew==",
+      "version": "10.4.18",
+      "resolved": "https://registry.npmjs.org/autoprefixer/-/autoprefixer-10.4.18.tgz",
+      "integrity": "sha512-1DKbDfsr6KUElM6wg+0zRNkB/Q7WcKYAaK+pzXn+Xqmszm/5Xa9coeNdtP88Vi+dPzZnMjhge8GIV49ZQkDa+g==",
      "funding": [
        {
          "type": "opencollective",
@@ -4283,7 +4283,7 @@
      ],
      "dependencies": {
        "browserslist": "^4.23.0",
-        "caniuse-lite": "^1.0.30001599",
+        "caniuse-lite": "^1.0.30001591",
        "fraction.js": "^4.3.7",
        "normalize-range": "^0.1.2",
        "picocolors": "^1.0.0",
@@ -4728,9 +4728,9 @@
      }
    },
    "node_modules/caniuse-lite": {
-      "version": "1.0.30001600",
-      "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001600.tgz",
-      "integrity": "sha512-+2S9/2JFhYmYaDpZvo0lKkfvuKIglrx68MwOBqMGHhQsNkLjB5xtc/TGoEPs+MxjSyN/72qer2g97nzR641mOQ==",
+      "version": "1.0.30001597",
+      "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001597.tgz",
+      "integrity": "sha512-7LjJvmQU6Sj7bL0j5b5WY/3n7utXUJvAe1lxhsHDbLmwX9mdL86Yjtr+5SRCyf8qME4M7pU2hswj0FpyBVCv9w==",
      "funding": [
        {
          "type": "opencollective",
@@ -12691,9 +12691,9 @@
      }
    },
    "node_modules/postcss": {
-      "version": "8.4.38",
-      "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.38.tgz",
-      "integrity": "sha512-Wglpdk03BSfXkHoQa3b/oulrotAkwrlLDRSOb9D0bN86FdRyE9lppSp33aHNPgBa0JKCoB+drFLZkQoRRYae5A==",
+      "version": "8.4.35",
+      "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.35.tgz",
+      "integrity": "sha512-u5U8qYpBCpN13BsiEB0CbR1Hhh4Gc0zLFuedrHJKMctHCHAGrMdG0PRM/KErzAL3CU6/eckEtmHNB3x6e3c0vA==",
      "funding": [
        {
          "type": "opencollective",
@@ -12711,7 +12711,7 @@
      "dependencies": {
        "nanoid": "^3.3.7",
        "picocolors": "^1.0.0",
-        "source-map-js": "^1.2.0"
+        "source-map-js": "^1.0.2"
      },
      "engines": {
        "node": "^10 || ^12 || >=14"
@@ -15295,9 +15295,9 @@
      }
    },
    "node_modules/source-map-js": {
-      "version": "1.2.0",
-      "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.0.tgz",
-      "integrity": "sha512-itJW8lvSA0TXEphiRoawsCksnlf8SyvmFzIhltqAHluXd88pkCd+cXJVHTDwdCr0IzwptSm035IHQktUu1QUMg==",
+      "version": "1.0.2",
+      "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.0.2.tgz",
+      "integrity": "sha512-R0XvVJ9WusLiqTCEiGCmICCMplcCkIwwR11mOSD9CR5u+IXYdiseeEuXCVAjS54zqwkLcPNnmU4OeJ6tUrWhDw==",
      "engines": {
        "node": ">=0.10.0"
      }
@@ -16141,9 +16141,9 @@
      }
    },
    "node_modules/typescript": {
-      "version": "5.4.3",
-      "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.4.3.tgz",
-      "integrity": "sha512-KrPd3PKaCLr78MalgiwJnA25Nm8HAmdwN3mYUYZgG/wizIo9EainNVQI9/yDavtVFRN2h3k8uf3GLHuhDMgEHg==",
+      "version": "5.4.2",
+      "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.4.2.tgz",
+      "integrity": "sha512-+2/g0Fds1ERlP6JsakQQDXjZdZMM+rqpamFZJEKh4kwTIn3iDkgKtby0CeNd5ATNZ4Ry1ax15TMx0W2V+miizQ==",
      "bin": {
        "tsc": "bin/tsc",
        "tsserver": "bin/tsserver"
@@ -10,10 +10,10 @@ function HomepageHeader() {
      <section className="text-center m-6 p-12 border border-red-400 rounded-[50px] bg-slate-200 dark:bg-immich-dark-gray">
        <img
          src={isDarkTheme ? 'img/immich-logo-stacked-dark.svg' : 'img/immich-logo-stacked-light.svg'}
-          className="md:h-60 h-44 mb-2 antialiased"
+          className="md:h-60 h-12 mb-2 antialiased"
          alt="Immich logo"
        />
-        <div className="sm:text-2xl text-lg md:text-4xl mb-12 sm:leading-tight">
+        <div className="sm:text-base md:text-4xl mb-12 sm:leading-tight">
          <p className="mb-1 font-medium text-immich-primary dark:text-immich-dark-primary">
            Self-hosted photo and <span className="block"></span>
            video management solution<span className="block"></span>
@@ -24,4 +24,3 @@
 /docs/features/user-management /docs/administration/user-management 301
 /docs/developer/contributing /docs/developer/pr-checklist 301
 /docs/guides/machine-learning /docs/guides/remote-machine-learning 301
-/docs/administration/password-login /docs/administration/system-settings 301
@@ -36,7 +36,7 @@ services:
    <<: *server-common

  redis:
-    image: redis:6.2-alpine@sha256:3fcb624d83a9c478357f16dc173c58ded325ccc5fd2a4375f3916c04cc579f70
+    image: redis:6.2-alpine@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5

  database:
    image: tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
@@ -1,6 +1,6 @@
 {
  "name": "immich-e2e",
-  "version": "1.100.0",
+  "version": "1.98.2",
  "description": "",
  "main": "index.js",
  "type": "module",
@@ -5,6 +5,7 @@ import {
  LibraryResponseDto,
  LoginResponseDto,
  SharedLinkType,
+  TimeBucketSize,
  getAllLibraries,
  getAssetInfo,
  updateAssets,
@@ -941,6 +942,146 @@ describe('/asset', () => {
    });
  });

+  describe('GET /asset/time-buckets', () => {
+    it('should require authentication', async () => {
+      const { status, body } = await request(app).get('/asset/time-buckets').query({ size: TimeBucketSize.Month });
+      expect(status).toBe(401);
+      expect(body).toEqual(errorDto.unauthorized);
+    });
+
+    it('should get time buckets by month', async () => {
+      const { status, body } = await request(app)
+        .get('/asset/time-buckets')
+        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
+        .query({ size: TimeBucketSize.Month });
+
+      expect(status).toBe(200);
+      expect(body).toEqual(
+        expect.arrayContaining([
+          { count: 3, timeBucket: '1970-02-01T00:00:00.000Z' },
+          { count: 1, timeBucket: '1970-01-01T00:00:00.000Z' },
+        ]),
+      );
+    });
+
+    it('should not allow access for unrelated shared links', async () => {
+      const sharedLink = await utils.createSharedLink(user1.accessToken, {
+        type: SharedLinkType.Individual,
+        assetIds: user1Assets.map(({ id }) => id),
+      });
+
+      const { status, body } = await request(app)
+        .get('/asset/time-buckets')
+        .query({ key: sharedLink.key, size: TimeBucketSize.Month });
+
+      expect(status).toBe(400);
+      expect(body).toEqual(errorDto.noPermission);
+    });
+
+    it('should get time buckets by day', async () => {
+      const { status, body } = await request(app)
+        .get('/asset/time-buckets')
+        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
+        .query({ size: TimeBucketSize.Day });
+
+      expect(status).toBe(200);
+      expect(body).toEqual([
+        { count: 2, timeBucket: '1970-02-11T00:00:00.000Z' },
+        { count: 1, timeBucket: '1970-02-10T00:00:00.000Z' },
+        { count: 1, timeBucket: '1970-01-01T00:00:00.000Z' },
+      ]);
+    });
+  });
+
+  describe('GET /asset/time-bucket', () => {
+    it('should require authentication', async () => {
+      const { status, body } = await request(app).get('/asset/time-bucket').query({
+        size: TimeBucketSize.Month,
+        timeBucket: '1900-01-01T00:00:00.000Z',
+      });
+
+      expect(status).toBe(401);
+      expect(body).toEqual(errorDto.unauthorized);
+    });
+
+    it('should handle 5 digit years', async () => {
+      const { status, body } = await request(app)
+        .get('/asset/time-bucket')
+        .query({ size: TimeBucketSize.Month, timeBucket: '+012345-01-01T00:00:00.000Z' })
+        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`);
+
+      expect(status).toBe(200);
+      expect(body).toEqual([]);
+    });
+
+    // TODO enable date string validation while still accepting 5 digit years
+    // it('should fail if time bucket is invalid', async () => {
+    //   const { status, body } = await request(app)
+    //     .get('/asset/time-bucket')
+    //     .set('Authorization', `Bearer ${user1.accessToken}`)
+    //     .query({ size: TimeBucketSize.Month, timeBucket: 'foo' });
+
+    //   expect(status).toBe(400);
+    //   expect(body).toEqual(errorDto.badRequest);
+    // });
+
+    it('should return time bucket', async () => {
+      const { status, body } = await request(app)
+        .get('/asset/time-bucket')
+        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
+        .query({ size: TimeBucketSize.Month, timeBucket: '1970-02-10T00:00:00.000Z' });
+
+      expect(status).toBe(200);
+      expect(body).toEqual([]);
+    });
+
+    it('should return error if time bucket is requested with partners asset and archived', async () => {
+      const req1 = await request(app)
+        .get('/asset/time-buckets')
+        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
+        .query({ size: TimeBucketSize.Month, withPartners: true, isArchived: true });
+
+      expect(req1.status).toBe(400);
+      expect(req1.body).toEqual(errorDto.badRequest());
+
+      const req2 = await request(app)
+        .get('/asset/time-buckets')
+        .set('Authorization', `Bearer ${user1.accessToken}`)
+        .query({ size: TimeBucketSize.Month, withPartners: true, isArchived: undefined });
+
+      expect(req2.status).toBe(400);
+      expect(req2.body).toEqual(errorDto.badRequest());
+    });
+
+    it('should return error if time bucket is requested with partners asset and favorite', async () => {
+      const req1 = await request(app)
+        .get('/asset/time-buckets')
+        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
+        .query({ size: TimeBucketSize.Month, withPartners: true, isFavorite: true });
+
+      expect(req1.status).toBe(400);
+      expect(req1.body).toEqual(errorDto.badRequest());
+
+      const req2 = await request(app)
+        .get('/asset/time-buckets')
+        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
+        .query({ size: TimeBucketSize.Month, withPartners: true, isFavorite: false });
+
+      expect(req2.status).toBe(400);
+      expect(req2.body).toEqual(errorDto.badRequest());
+    });
+
+    it('should return error if time bucket is requested with partners asset and trash', async () => {
+      const req = await request(app)
+        .get('/asset/time-buckets')
+        .set('Authorization', `Bearer ${user1.accessToken}`)
+        .query({ size: TimeBucketSize.Month, withPartners: true, isTrashed: true });
+
+      expect(req.status).toBe(400);
+      expect(req.body).toEqual(errorDto.badRequest());
+    });
+  });
+
  describe('GET /asset', () => {
    it('should return stack data', async () => {
      const { status, body } = await request(app).get('/asset').set('Authorization', `Bearer ${stackUser.accessToken}`);
@@ -12,8 +12,7 @@ describe('/audit', () => {
    admin = await utils.adminSetup();
  });

-  // TODO: Enable these tests again once #7436 is resolved as these were flaky
-  describe.skip('GET :/file-report', () => {
+  describe('GET :/file-report', () => {
    it('excludes assets without issues from report', async () => {
      const [trashedAsset, archivedAsset] = await Promise.all([
        utils.createAsset(admin.accessToken),
@@ -27,7 +27,7 @@ describe('/library', () => {
    await utils.resetDatabase();
    admin = await utils.adminSetup();
    user = await utils.userSetup(admin.accessToken, userDto.user1);
-    library = await utils.createLibrary(admin.accessToken, { ownerId: admin.userId, type: LibraryType.External });
+    library = await utils.createLibrary(admin.accessToken, { type: LibraryType.External });
    websocket = await utils.connectWebsocket(admin.accessToken);
  });

@@ -82,7 +82,7 @@ describe('/library', () => {
      const { status, body } = await request(app)
        .post('/library')
        .set('Authorization', `Bearer ${user.accessToken}`)
-        .send({ ownerId: admin.userId, type: LibraryType.External });
+        .send({ type: LibraryType.External });

      expect(status).toBe(403);
      expect(body).toEqual(errorDto.forbidden);
@@ -92,7 +92,7 @@ describe('/library', () => {
      const { status, body } = await request(app)
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
-        .send({ ownerId: admin.userId, type: LibraryType.External });
+        .send({ type: LibraryType.External });

      expect(status).toBe(201);
      expect(body).toEqual(
@@ -113,7 +113,6 @@ describe('/library', () => {
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
        .send({
-          ownerId: admin.userId,
          type: LibraryType.External,
          name: 'My Awesome Library',
          importPaths: ['/path/to/import'],
@@ -134,7 +133,6 @@ describe('/library', () => {
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
        .send({
-          ownerId: admin.userId,
          type: LibraryType.External,
          name: 'My Awesome Library',
          importPaths: ['/path', '/path'],
@@ -150,7 +148,6 @@ describe('/library', () => {
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
        .send({
-          ownerId: admin.userId,
          type: LibraryType.External,
          name: 'My Awesome Library',
          importPaths: ['/path/to/import'],
@@ -165,7 +162,7 @@ describe('/library', () => {
      const { status, body } = await request(app)
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
-        .send({ ownerId: admin.userId, type: LibraryType.Upload });
+        .send({ type: LibraryType.Upload });

      expect(status).toBe(201);
      expect(body).toEqual(
@@ -185,7 +182,7 @@ describe('/library', () => {
      const { status, body } = await request(app)
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
-        .send({ ownerId: admin.userId, type: LibraryType.Upload, name: 'My Awesome Library' });
+        .send({ type: LibraryType.Upload, name: 'My Awesome Library' });

      expect(status).toBe(201);
      expect(body).toEqual(
@@ -199,7 +196,7 @@ describe('/library', () => {
      const { status, body } = await request(app)
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
-        .send({ ownerId: admin.userId, type: LibraryType.Upload, importPaths: ['/path/to/import'] });
+        .send({ type: LibraryType.Upload, importPaths: ['/path/to/import'] });

      expect(status).toBe(400);
      expect(body).toEqual(errorDto.badRequest('Upload libraries cannot have import paths'));
@@ -209,7 +206,7 @@ describe('/library', () => {
      const { status, body } = await request(app)
        .post('/library')
        .set('Authorization', `Bearer ${admin.accessToken}`)
-        .send({ ownerId: admin.userId, type: LibraryType.Upload, exclusionPatterns: ['**/Raw/**'] });
+        .send({ type: LibraryType.Upload, exclusionPatterns: ['**/Raw/**'] });

      expect(status).toBe(400);
      expect(body).toEqual(errorDto.badRequest('Upload libraries cannot have exclusion patterns'));
@@ -333,10 +330,7 @@ describe('/library', () => {
    });

    it('should get library by id', async () => {
-      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
-        type: LibraryType.External,
-      });
+      const library = await utils.createLibrary(admin.accessToken, { type: LibraryType.External });

      const { status, body } = await request(app)
        .get(`/library/${library.id}`)
@@ -392,10 +386,7 @@ describe('/library', () => {
    });

    it('should delete an external library', async () => {
-      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
-        type: LibraryType.External,
-      });
+      const library = await utils.createLibrary(admin.accessToken, { type: LibraryType.External });

      const { status, body } = await request(app)
        .delete(`/library/${library.id}`)
@@ -416,7 +407,6 @@ describe('/library', () => {

    it('should delete an external library with assets', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
        type: LibraryType.External,
        importPaths: [`${testAssetDirInternal}/temp`],
      });
@@ -465,7 +455,6 @@ describe('/library', () => {

    it('should not scan an upload library', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
        type: LibraryType.Upload,
      });

@@ -479,7 +468,6 @@ describe('/library', () => {

    it('should scan external library', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
        type: LibraryType.External,
        importPaths: [`${testAssetDirInternal}/temp/directoryA`],
      });
@@ -495,7 +483,6 @@ describe('/library', () => {

    it('should scan external library with exclusion pattern', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
        type: LibraryType.External,
        importPaths: [`${testAssetDirInternal}/temp`],
        exclusionPatterns: ['**/directoryA'],
@@ -512,7 +499,6 @@ describe('/library', () => {

    it('should scan multiple import paths', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
        type: LibraryType.External,
        importPaths: [`${testAssetDirInternal}/temp/directoryA`, `${testAssetDirInternal}/temp/directoryB`],
      });
@@ -529,7 +515,6 @@ describe('/library', () => {

    it('should pick up new files', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
-        ownerId: admin.userId,
        type: LibraryType.External,
        importPaths: [`${testAssetDirInternal}/temp`],
      });
@@ -1,4 +1,4 @@
-import { AssetFileUploadResponseDto, LoginResponseDto, deleteAssets, updateAsset } from '@immich/sdk';
+import { AssetFileUploadResponseDto, LoginResponseDto, deleteAssets } from '@immich/sdk';
 import { DateTime } from 'luxon';
 import { readFile } from 'node:fs/promises';
 import { join } from 'node:path';
@@ -7,6 +7,7 @@ import { errorDto } from 'src/responses';
 import { app, asBearerAuth, testAssetDir, utils } from 'src/utils';
 import request from 'supertest';
 import { afterAll, beforeAll, describe, expect, it } from 'vitest';
+
 const today = DateTime.now();

 describe('/search', () => {
@@ -18,7 +19,7 @@ describe('/search', () => {
  let assetCyclamen: AssetFileUploadResponseDto;
  let assetNotocactus: AssetFileUploadResponseDto;
  let assetSilver: AssetFileUploadResponseDto;
-  let assetDensity: AssetFileUploadResponseDto;
+  // let assetDensity: AssetFileUploadResponseDto;
  // let assetPhiladelphia: AssetFileUploadResponseDto;
  // let assetOrychophragmus: AssetFileUploadResponseDto;
  // let assetRidge: AssetFileUploadResponseDto;
@@ -78,37 +79,6 @@ describe('/search', () => {
      await utils.waitForWebsocketEvent({ event: 'assetUpload', id: asset.id });
    }

-    // note: the coordinates here are not the actual coordinates of the images and are random for most of them
-    const cities = [
-      { latitude: 48.853_41, longitude: 2.3488 }, // paris
-      { latitude: 63.0695, longitude: -151.0074 }, // denali
-      { latitude: 52.524_37, longitude: 13.410_53 }, // berlin
-      { latitude: 1.314_663_1, longitude: 103.845_409_3 }, // singapore
-      { latitude: 41.013_84, longitude: 28.949_66 }, // istanbul
-      { latitude: 5.556_02, longitude: -0.1969 }, // accra
-      { latitude: 37.544_270_6, longitude: -4.727_752_8 }, // andalusia
-      { latitude: 23.133_02, longitude: -82.383_04 }, // havana
-      { latitude: 41.694_11, longitude: 44.833_68 }, // tbilisi
-      { latitude: 31.222_22, longitude: 121.458_06 }, // shanghai
-      { latitude: 47.040_57, longitude: 9.068_04 }, // glarus
-      { latitude: 38.9711, longitude: -109.7137 }, // thompson springs
-      { latitude: 40.714_27, longitude: -74.005_97 }, // new york
-      { latitude: 32.771_52, longitude: -89.116_73 }, // philadelphia
-      { latitude: 31.634_16, longitude: -7.999_94 }, // marrakesh
-      { latitude: 38.523_735_4, longitude: -78.488_619_4 }, // tanners ridge
-      { latitude: 59.938_63, longitude: 30.314_13 }, // st. petersburg
-      { latitude: 35.6895, longitude: 139.691_71 }, // tokyo
-    ];
-
-    const updates = assets.map((asset, i) =>
-      updateAsset({ id: asset.id, updateAssetDto: cities[i] }, { headers: asBearerAuth(admin.accessToken) }),
-    );
-
-    await Promise.all(updates);
-    for (const asset of assets) {
-      await utils.waitForWebsocketEvent({ event: 'assetUpdate', id: asset.id });
-    }
-
    [
      assetFalcon,
      assetDenali,
@@ -122,7 +92,7 @@ describe('/search', () => {
      assetOneJpg5,
      assetGlarus,
      assetSprings,
-      assetDensity,
+      // assetDensity,
      // assetPhiladelphia,
      // assetOrychophragmus,
      // assetRidge,
@@ -136,7 +106,7 @@ describe('/search', () => {
  });

  afterAll(async () => {
-    utils.disconnectWebsocket(websocket);
+    await utils.disconnectWebsocket(websocket);
  });

  describe('POST /search/metadata', () => {
@@ -328,15 +298,15 @@ describe('/search', () => {
      },
      {
        should: 'should search by city',
-        deferred: () => ({ dto: { city: 'Accra' }, assets: [assetHeic] }),
+        deferred: () => ({ dto: { city: 'Ralston' }, assets: [assetHeic] }),
      },
      {
        should: 'should search by state',
-        deferred: () => ({ dto: { state: 'New York' }, assets: [assetDensity] }),
+        deferred: () => ({ dto: { state: 'Douglas County, Nebraska' }, assets: [assetHeic] }),
      },
      {
        should: 'should search by country',
-        deferred: () => ({ dto: { country: 'France' }, assets: [assetFalcon] }),
+        deferred: () => ({ dto: { country: 'United States of America' }, assets: [assetHeic] }),
      },
      {
        should: 'should search by make',
@@ -400,44 +370,13 @@ describe('/search', () => {
      expect(body).toEqual(errorDto.unauthorized);
    });

-    it('should get relevant places', async () => {
-      const name = 'Paris';
-
+    it('should get places', async () => {
      const { status, body } = await request(app)
-        .get(`/search/places?name=${name}`)
+        .get('/search/places?name=Paris')
        .set('Authorization', `Bearer ${admin.accessToken}`);
-
      expect(status).toBe(200);
      expect(Array.isArray(body)).toBe(true);
-      if (Array.isArray(body)) {
-        expect(body.length).toBeGreaterThan(10);
-        expect(body[0].name).toEqual(name);
-        expect(body[0].admin2name).toEqual(name);
-      }
-    });
-  });
-
-  describe('GET /search/cities', () => {
-    it('should require authentication', async () => {
-      const { status, body } = await request(app).get('/search/cities');
-      expect(status).toBe(401);
-      expect(body).toEqual(errorDto.unauthorized);
-    });
-
-    it('should get all cities', async () => {
-      const { status, body } = await request(app)
-        .get('/search/cities')
-        .set('Authorization', `Bearer ${admin.accessToken}`);
-
-      expect(status).toBe(200);
-      expect(Array.isArray(body)).toBe(true);
-      if (Array.isArray(body)) {
-        expect(body.length).toBeGreaterThan(10);
-        const assetsWithCity = body.filter((asset) => !!asset.exifInfo?.city);
-        expect(assetsWithCity.length).toEqual(body.length);
-        const cities = new Set(assetsWithCity.map((asset) => asset.exifInfo.city));
-        expect(cities.size).toEqual(body.length);
-      }
+      expect(body.length).toBeGreaterThan(10);
    });
  });

@@ -452,21 +391,7 @@ describe('/search', () => {
      const { status, body } = await request(app)
        .get('/search/suggestions?type=country')
        .set('Authorization', `Bearer ${admin.accessToken}`);
-      expect(body).toEqual([
-        'Cuba',
-        'France',
-        'Georgia',
-        'Germany',
-        'Ghana',
-        'Japan',
-        'Morocco',
-        "People's Republic of China",
-        'Russian Federation',
-        'Singapore',
-        'Spain',
-        'Switzerland',
-        'United States of America',
-      ]);
+      expect(body).toEqual(['United States of America']);
      expect(status).toBe(200);
    });

@@ -474,23 +399,7 @@ describe('/search', () => {
      const { status, body } = await request(app)
        .get('/search/suggestions?type=state')
        .set('Authorization', `Bearer ${admin.accessToken}`);
-      expect(body).toEqual([
-        'Accra, Greater Accra',
-        'Berlin',
-        'Glarus, Glarus',
-        'Havana',
-        'Marrakech, Marrakesh-Safi',
-        'Mesa County, Colorado',
-        'Neshoba County, Mississippi',
-        'New York',
-        'Page County, Virginia',
-        'Paris, Île-de-France',
-        'Province of Córdoba, Andalusia',
-        'Shanghai Municipality, Shanghai',
-        'St.-Petersburg',
-        'Tbilisi',
-        'Tokyo',
-      ]);
+      expect(body).toEqual(['Douglas County, Nebraska', 'Mesa County, Colorado']);
      expect(status).toBe(200);
    });

@@ -498,24 +407,7 @@ describe('/search', () => {
      const { status, body } = await request(app)
        .get('/search/suggestions?type=city')
        .set('Authorization', `Bearer ${admin.accessToken}`);
-      expect(body).toEqual([
-        'Accra',
-        'Berlin',
-        'Glarus',
-        'Havana',
-        'Marrakesh',
-        'Montalbán de Córdoba',
-        'New York City',
-        'Palisade',
-        'Paris',
-        'Philadelphia',
-        'Saint Petersburg',
-        'Shanghai',
-        'Singapore',
-        'Stanley',
-        'Tbilisi',
-        'Tokyo',
-      ]);
+      expect(body).toEqual(['Palisade', 'Ralston']);
      expect(status).toBe(200);
    });

@@ -1,23 +1,18 @@
-import { AssetFileUploadResponseDto, LoginResponseDto, SharedLinkType, getConfig } from '@immich/sdk';
+import { LoginResponseDto } from '@immich/sdk';
 import { createUserDto } from 'src/fixtures';
 import { errorDto } from 'src/responses';
-import { app, asBearerAuth, utils } from 'src/utils';
+import { app, utils } from 'src/utils';
 import request from 'supertest';
 import { beforeAll, describe, expect, it } from 'vitest';

-const getSystemConfig = (accessToken: string) => getConfig({ headers: asBearerAuth(accessToken) });
-
 describe('/system-config', () => {
  let admin: LoginResponseDto;
  let nonAdmin: LoginResponseDto;
-  let asset: AssetFileUploadResponseDto;

  beforeAll(async () => {
    await utils.resetDatabase();
    admin = await utils.adminSetup();
    nonAdmin = await utils.userSetup(admin.accessToken, createUserDto.user1);
-
-    asset = await utils.createAsset(admin.accessToken);
  });

  describe('GET /system-config/map/style.json', () => {
@@ -27,19 +22,6 @@ describe('/system-config', () => {
      expect(body).toEqual(errorDto.unauthorized);
    });

-    it('should allow shared link access', async () => {
-      const sharedLink = await utils.createSharedLink(admin.accessToken, {
-        type: SharedLinkType.Individual,
-        assetIds: [asset.id],
-      });
-      const { status, body } = await request(app)
-        .get(`/system-config/map/style.json?key=${sharedLink.key}`)
-        .query({ theme: 'dark' });
-
-      expect(status).toBe(200);
-      expect(body).toEqual(expect.objectContaining({ id: 'immich-map-dark' }));
-    });
-
    it('should throw an error if a theme is not light or dark', async () => {
      for (const theme of ['dark1', true, 123, '', null, undefined]) {
        const { status, body } = await request(app)
@@ -78,25 +60,4 @@ describe('/system-config', () => {
      expect(body).toEqual(expect.objectContaining({ id: 'immich-map-dark' }));
    });
  });
-
-  describe('PUT /system-config', () => {
-    it('should require authentication', async () => {
-      const { status, body } = await request(app).put('/system-config');
-      expect(status).toBe(401);
-      expect(body).toEqual(errorDto.unauthorized);
-    });
-
-    it('should reject an invalid config entry', async () => {
-      const { status, body } = await request(app)
-        .put('/system-config')
-        .set('Authorization', `Bearer ${admin.accessToken}`)
-        .send({
-          ...(await getSystemConfig(admin.accessToken)),
-          storageTemplate: { enabled: true, hashVerificationEnabled: true, template: '{{foo}}' },
-        });
-
-      expect(status).toBe(400);
-      expect(body).toEqual(errorDto.badRequest(expect.stringContaining('Invalid storage template')));
-    });
-  });
 });
@@ -1,193 +0,0 @@
-import { AssetFileUploadResponseDto, LoginResponseDto, SharedLinkType, TimeBucketSize } from '@immich/sdk';
-import { DateTime } from 'luxon';
-import { createUserDto } from 'src/fixtures';
-import { errorDto } from 'src/responses';
-import { app, utils } from 'src/utils';
-import request from 'supertest';
-import { beforeAll, describe, expect, it } from 'vitest';
-
-// TODO this should probably be a test util function
-const today = DateTime.fromObject({
-  year: 2023,
-  month: 11,
-  day: 3,
-}) as DateTime<true>;
-const yesterday = today.minus({ days: 1 });
-
-describe('/timeline', () => {
-  let admin: LoginResponseDto;
-  let user: LoginResponseDto;
-  let timeBucketUser: LoginResponseDto;
-
-  let userAssets: AssetFileUploadResponseDto[];
-
-  beforeAll(async () => {
-    await utils.resetDatabase();
-    admin = await utils.adminSetup({ onboarding: false });
-    [user, timeBucketUser] = await Promise.all([
-      utils.userSetup(admin.accessToken, createUserDto.create('1')),
-      utils.userSetup(admin.accessToken, createUserDto.create('time-bucket')),
-    ]);
-
-    userAssets = await Promise.all([
-      utils.createAsset(user.accessToken),
-      utils.createAsset(user.accessToken),
-      utils.createAsset(user.accessToken, {
-        isFavorite: true,
-        isReadOnly: true,
-        fileCreatedAt: yesterday.toISO(),
-        fileModifiedAt: yesterday.toISO(),
-        assetData: { filename: 'example.mp4' },
-      }),
-      utils.createAsset(user.accessToken),
-      utils.createAsset(user.accessToken),
-    ]);
-
-    await Promise.all([
-      utils.createAsset(timeBucketUser.accessToken, { fileCreatedAt: new Date('1970-01-01').toISOString() }),
-      utils.createAsset(timeBucketUser.accessToken, { fileCreatedAt: new Date('1970-02-10').toISOString() }),
-      utils.createAsset(timeBucketUser.accessToken, { fileCreatedAt: new Date('1970-02-11').toISOString() }),
-      utils.createAsset(timeBucketUser.accessToken, { fileCreatedAt: new Date('1970-02-11').toISOString() }),
-    ]);
-  });
-
-  describe('GET /timeline/buckets', () => {
-    it('should require authentication', async () => {
-      const { status, body } = await request(app).get('/timeline/buckets').query({ size: TimeBucketSize.Month });
-      expect(status).toBe(401);
-      expect(body).toEqual(errorDto.unauthorized);
-    });
-
-    it('should get time buckets by month', async () => {
-      const { status, body } = await request(app)
-        .get('/timeline/buckets')
-        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
-        .query({ size: TimeBucketSize.Month });
-
-      expect(status).toBe(200);
-      expect(body).toEqual(
-        expect.arrayContaining([
-          { count: 3, timeBucket: '1970-02-01T00:00:00.000Z' },
-          { count: 1, timeBucket: '1970-01-01T00:00:00.000Z' },
-        ]),
-      );
-    });
-
-    it('should not allow access for unrelated shared links', async () => {
-      const sharedLink = await utils.createSharedLink(user.accessToken, {
-        type: SharedLinkType.Individual,
-        assetIds: userAssets.map(({ id }) => id),
-      });
-
-      const { status, body } = await request(app)
-        .get('/timeline/buckets')
-        .query({ key: sharedLink.key, size: TimeBucketSize.Month });
-
-      expect(status).toBe(400);
-      expect(body).toEqual(errorDto.noPermission);
-    });
-
-    it('should get time buckets by day', async () => {
-      const { status, body } = await request(app)
-        .get('/timeline/buckets')
-        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
-        .query({ size: TimeBucketSize.Day });
-
-      expect(status).toBe(200);
-      expect(body).toEqual([
-        { count: 2, timeBucket: '1970-02-11T00:00:00.000Z' },
-        { count: 1, timeBucket: '1970-02-10T00:00:00.000Z' },
-        { count: 1, timeBucket: '1970-01-01T00:00:00.000Z' },
-      ]);
-    });
-
-    it('should return error if time bucket is requested with partners asset and archived', async () => {
-      const req1 = await request(app)
-        .get('/timeline/buckets')
-        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
-        .query({ size: TimeBucketSize.Month, withPartners: true, isArchived: true });
-
-      expect(req1.status).toBe(400);
-      expect(req1.body).toEqual(errorDto.badRequest());
-
-      const req2 = await request(app)
-        .get('/timeline/buckets')
-        .set('Authorization', `Bearer ${user.accessToken}`)
-        .query({ size: TimeBucketSize.Month, withPartners: true, isArchived: undefined });
-
-      expect(req2.status).toBe(400);
-      expect(req2.body).toEqual(errorDto.badRequest());
-    });
-
-    it('should return error if time bucket is requested with partners asset and favorite', async () => {
-      const req1 = await request(app)
-        .get('/timeline/buckets')
-        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
-        .query({ size: TimeBucketSize.Month, withPartners: true, isFavorite: true });
-
-      expect(req1.status).toBe(400);
-      expect(req1.body).toEqual(errorDto.badRequest());
-
-      const req2 = await request(app)
-        .get('/timeline/buckets')
-        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
-        .query({ size: TimeBucketSize.Month, withPartners: true, isFavorite: false });
-
-      expect(req2.status).toBe(400);
-      expect(req2.body).toEqual(errorDto.badRequest());
-    });
-
-    it('should return error if time bucket is requested with partners asset and trash', async () => {
-      const req = await request(app)
-        .get('/timeline/buckets')
-        .set('Authorization', `Bearer ${user.accessToken}`)
-        .query({ size: TimeBucketSize.Month, withPartners: true, isTrashed: true });
-
-      expect(req.status).toBe(400);
-      expect(req.body).toEqual(errorDto.badRequest());
-    });
-  });
-
-  describe('GET /timeline/bucket', () => {
-    it('should require authentication', async () => {
-      const { status, body } = await request(app).get('/timeline/bucket').query({
-        size: TimeBucketSize.Month,
-        timeBucket: '1900-01-01T00:00:00.000Z',
-      });
-
-      expect(status).toBe(401);
-      expect(body).toEqual(errorDto.unauthorized);
-    });
-
-    it('should handle 5 digit years', async () => {
-      const { status, body } = await request(app)
-        .get('/timeline/bucket')
-        .query({ size: TimeBucketSize.Month, timeBucket: '+012345-01-01T00:00:00.000Z' })
-        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`);
-
-      expect(status).toBe(200);
-      expect(body).toEqual([]);
-    });
-
-    // TODO enable date string validation while still accepting 5 digit years
-    // it('should fail if time bucket is invalid', async () => {
-    //   const { status, body } = await request(app)
-    //     .get('/timeline/bucket')
-    //     .set('Authorization', `Bearer ${user.accessToken}`)
-    //     .query({ size: TimeBucketSize.Month, timeBucket: 'foo' });
-
-    //   expect(status).toBe(400);
-    //   expect(body).toEqual(errorDto.badRequest);
-    // });
-
-    it('should return time bucket', async () => {
-      const { status, body } = await request(app)
-        .get('/timeline/bucket')
-        .set('Authorization', `Bearer ${timeBucketUser.accessToken}`)
-        .query({ size: TimeBucketSize.Month, timeBucket: '1970-02-10T00:00:00.000Z' });
-
-      expect(status).toBe(200);
-      expect(body).toEqual([]);
-    });
-  });
-});
@@ -2,25 +2,25 @@ import { stat } from 'node:fs/promises';
 import { app, immichCli, utils } from 'src/utils';
 import { beforeEach, describe, expect, it } from 'vitest';

-describe(`immich login`, () => {
+describe(`immich login-key`, () => {
  beforeEach(async () => {
    await utils.resetDatabase();
  });

  it('should require a url', async () => {
-    const { stderr, exitCode } = await immichCli(['login']);
+    const { stderr, exitCode } = await immichCli(['login-key']);
    expect(stderr).toBe("error: missing required argument 'url'");
    expect(exitCode).toBe(1);
  });

  it('should require a key', async () => {
-    const { stderr, exitCode } = await immichCli(['login', app]);
+    const { stderr, exitCode } = await immichCli(['login-key', app]);
    expect(stderr).toBe("error: missing required argument 'key'");
    expect(exitCode).toBe(1);
  });

  it('should require a valid key', async () => {
-    const { stderr, exitCode } = await immichCli(['login', app, 'immich-is-so-cool']);
+    const { stderr, exitCode } = await immichCli(['login-key', app, 'immich-is-so-cool']);
    expect(stderr).toContain('Failed to connect to server');
    expect(stderr).toContain('Invalid API key');
    expect(stderr).toContain('401');
@@ -30,7 +30,7 @@ describe(`immich login`, () => {
  it('should login and save auth.yml with 600', async () => {
    const admin = await utils.adminSetup();
    const key = await utils.createApiKey(admin.accessToken);
-    const { stdout, stderr, exitCode } = await immichCli(['login', app, `${key.secret}`]);
+    const { stdout, stderr, exitCode } = await immichCli(['login-key', app, `${key.secret}`]);
    expect(stdout.split('\n')).toEqual([
      'Logging in to http://127.0.0.1:2283/api',
      'Logged in as admin@immich.cloud',
@@ -47,7 +47,7 @@ describe(`immich login`, () => {
  it('should login without /api in the url', async () => {
    const admin = await utils.adminSetup();
    const key = await utils.createApiKey(admin.accessToken);
-    const { stdout, stderr, exitCode } = await immichCli(['login', app.replaceAll('/api', ''), `${key.secret}`]);
+    const { stdout, stderr, exitCode } = await immichCli(['login-key', app.replaceAll('/api', ''), `${key.secret}`]);
    expect(stdout.split('\n')).toEqual([
      'Logging in to http://127.0.0.1:2283',
      'Discovered API at http://127.0.0.1:2283/api',
@@ -4,23 +4,19 @@ import { beforeAll, describe, expect, it } from 'vitest';
 describe(`immich server-info`, () => {
  beforeAll(async () => {
    await utils.resetDatabase();
-    const admin = await utils.adminSetup();
-    await utils.cliLogin(admin.accessToken);
+    await utils.cliLogin();
  });

  it('should return the server info', async () => {
    const { stderr, stdout, exitCode } = await immichCli(['server-info']);
    expect(stdout.split('\n')).toEqual([
-      expect.stringContaining('Server Info (via admin@immich.cloud'),
-      '  Url: http://127.0.0.1:2283/api',
-      expect.stringContaining('Version:'),
-      '  Formats:',
-      expect.stringContaining('Images:'),
-      expect.stringContaining('Videos:'),
-      '  Statistics:',
-      '    Images: 0',
-      '    Videos: 0',
-      '    Total: 0',
+      expect.stringContaining('Server Version:'),
+      expect.stringContaining('Image Types:'),
+      expect.stringContaining('Video Types:'),
+      'Statistics:',
+      '  Images: 0',
+      '  Videos: 0',
+      '  Total: 0',
    ]);
    expect(stderr).toBe('');
    expect(exitCode).toBe(0);
@@ -1,69 +1,20 @@
-import { LoginResponseDto, getAllAlbums, getAllAssets } from '@immich/sdk';
+import { getAllAlbums, getAllAssets } from '@immich/sdk';
 import { mkdir, readdir, rm, symlink } from 'node:fs/promises';
 import { asKeyAuth, immichCli, testAssetDir, utils } from 'src/utils';
 import { beforeAll, beforeEach, describe, expect, it } from 'vitest';

 describe(`immich upload`, () => {
-  let admin: LoginResponseDto;
  let key: string;

  beforeAll(async () => {
    await utils.resetDatabase();
-
-    admin = await utils.adminSetup();
-    key = await utils.cliLogin(admin.accessToken);
+    key = await utils.cliLogin();
  });

  beforeEach(async () => {
    await utils.resetDatabase(['assets', 'albums']);
  });

-  describe(`immich upload /path/to/file.jpg`, () => {
-    it('should upload a single file', async () => {
-      const { stderr, stdout, exitCode } = await immichCli(['upload', `${testAssetDir}/albums/nature/silver_fir.jpg`]);
-      expect(stderr).toBe('');
-      expect(stdout.split('\n')).toEqual(
-        expect.arrayContaining([expect.stringContaining('Successfully uploaded 1 asset')]),
-      );
-      expect(exitCode).toBe(0);
-
-      const assets = await getAllAssets({}, { headers: asKeyAuth(key) });
-      expect(assets.length).toBe(1);
-    });
-
-    it('should skip a duplicate file', async () => {
-      const first = await immichCli(['upload', `${testAssetDir}/albums/nature/silver_fir.jpg`]);
-      expect(first.stderr).toBe('');
-      expect(first.stdout.split('\n')).toEqual(
-        expect.arrayContaining([expect.stringContaining('Successfully uploaded 1 asset')]),
-      );
-      expect(first.exitCode).toBe(0);
-
-      const assets = await getAllAssets({}, { headers: asKeyAuth(key) });
-      expect(assets.length).toBe(1);
-
-      const second = await immichCli(['upload', `${testAssetDir}/albums/nature/silver_fir.jpg`]);
-      expect(second.stderr).toBe('');
-      expect(second.stdout.split('\n')).toEqual(
-        expect.arrayContaining([
-          expect.stringContaining('Found 0 new files and 1 duplicate'),
-          expect.stringContaining('All assets were already uploaded, nothing to do'),
-        ]),
-      );
-      expect(first.exitCode).toBe(0);
-    });
-
-    it('should skip files that do not exist', async () => {
-      const { stderr, stdout, exitCode } = await immichCli(['upload', `/path/to/file`]);
-      expect(stderr).toBe('');
-      expect(stdout.split('\n')).toEqual(expect.arrayContaining([expect.stringContaining('No files found, exiting')]));
-      expect(exitCode).toBe(0);
-
-      const assets = await getAllAssets({}, { headers: asKeyAuth(key) });
-      expect(assets.length).toBe(0);
-    });
-  });
-
  describe('immich upload --recursive', () => {
    it('should upload a folder recursively', async () => {
      const { stderr, stdout, exitCode } = await immichCli(['upload', `${testAssetDir}/albums/nature/`, '--recursive']);
@@ -39,7 +39,7 @@ import { makeRandomImage } from 'src/generators';
 import request from 'supertest';

 type CliResponse = { stdout: string; stderr: string; exitCode: number | null };
-type EventType = 'assetUpload' | 'assetUpdate' | 'assetDelete' | 'userDelete';
+type EventType = 'assetUpload' | 'assetDelete' | 'userDelete';
 type WaitOptions = { event: EventType; id?: string; total?: number; timeout?: number };
 type AdminSetupOptions = { onboarding?: boolean };
 type AssetData = { bytes?: Buffer; filename: string };
@@ -82,7 +82,6 @@ let client: pg.Client | null = null;

 const events: Record<EventType, Set<string>> = {
  assetUpload: new Set<string>(),
-  assetUpdate: new Set<string>(),
  assetDelete: new Set<string>(),
  userDelete: new Set<string>(),
 };
@@ -186,7 +185,6 @@ export const utils = {
      websocket
        .on('connect', () => resolve(websocket))
        .on('on_upload_success', (data: AssetResponseDto) => onEvent({ event: 'assetUpload', id: data.id }))
-        .on('on_asset_update', (data: AssetResponseDto) => onEvent({ event: 'assetUpdate', id: data.id }))
        .on('on_asset_delete', (assetId: string) => onEvent({ event: 'assetDelete', id: assetId }))
        .on('on_user_delete', (userId: string) => onEvent({ event: 'userDelete', id: userId }))
        .connect();
@@ -406,9 +404,10 @@ export const utils = {
      },
    ]),

-  cliLogin: async (accessToken: string) => {
-    const key = await utils.createApiKey(accessToken);
-    await immichCli(['login', app, `${key.secret}`]);
+  cliLogin: async () => {
+    const admin = await utils.adminSetup();
+    const key = await utils.createApiKey(admin.accessToken);
+    await immichCli(['login-key', app, `${key.secret}`]);
    return key.secret;
  },
 };
@@ -6,7 +6,7 @@ ip_address=$(hostname -I | awk '{print $1}')

 create_immich_directory() {
  echo "Creating Immich directory..."
-  mkdir -p ./immich-app
+  mkdir -p ./immich-app/immich-data
  cd ./immich-app || exit
 }

@@ -20,6 +20,21 @@ download_dot_env_file() {
  curl -L https://github.com/immich-app/immich/releases/latest/download/example.env -o ./.env >/dev/null 2>&1
 }

+replace_env_value() {
+  KERNEL="$(uname -s | tr '[:upper:]' '[:lower:]')"
+  if [ "$KERNEL" = "darwin" ]; then
+    sed -i '' "s|$1=.*|$1=$2|" ./.env
+  else
+    sed -i "s|$1=.*|$1=$2|" ./.env
+  fi
+}
+
+populate_upload_location() {
+  echo "Populating default UPLOAD_LOCATION value..."
+  upload_location=$(pwd)/immich-data
+  replace_env_value "UPLOAD_LOCATION" "$upload_location"
+}
+
 start_docker_compose() {
  echo "Starting Immich's docker containers"

@@ -44,6 +59,7 @@ start_docker_compose() {
 show_friendly_message() {
  echo "Successfully deployed Immich!"
  echo "You can access the website at http://$ip_address:2283 and the server URL for the mobile app is http://$ip_address:2283/api"
+  echo "The library location is $upload_location"
  echo "---------------------------------------------------"
  echo "If you want to configure custom information of the server, including the database, Redis information, or the backup (or upload) location, etc. 
  
@@ -59,4 +75,5 @@ show_friendly_message() {
 create_immich_directory
 download_docker_compose_file
 download_dot_env_file
+populate_upload_location
 start_docker_compose
@@ -1,8 +1,8 @@
 ARG DEVICE=cpu

-FROM python:3.11-bookworm@sha256:e2ed446c899827ed992f8a5a8875fa0853fcab32581e61418b650322061aa3c4 as builder-cpu
+FROM python:3.11-bookworm@sha256:8e697181d24bd77cc4251fdd37e4cdd6d725c5de2ed63b9bc8db77357400c5e2 as builder-cpu

-FROM openvino/ubuntu22_runtime:2023.3.0@sha256:176646df619032ea6c10faf842867119c393e7497b7f88b5e307e932a0fd5aa8 as builder-openvino
+FROM openvino/ubuntu22_runtime:2023.1.0@sha256:002842a9005ba01543b7169ff6f14ecbec82287f09c4d1dd37717f0a8e8754a7 as builder-openvino
 USER root
 RUN apt-get update && apt-get install -y --no-install-recommends python3-dev

@@ -21,12 +21,10 @@ FROM builder-${DEVICE} as builder

 ARG DEVICE
 ENV PYTHONDONTWRITEBYTECODE=1 \
-    PYTHONUNBUFFERED=1 \
-    PIP_NO_CACHE_DIR=true \
-    VIRTUAL_ENV="/opt/venv" \
-    PATH="/opt/venv/bin:${PATH}"
-
-RUN apt-get update && apt-get install -y --no-install-recommends g++
+  PYTHONUNBUFFERED=1 \
+  PIP_NO_CACHE_DIR=true \
+  VIRTUAL_ENV="/opt/venv" \
+  PATH="/opt/venv/bin:${PATH}"

 RUN pip install --upgrade pip && pip install poetry
 RUN poetry config installer.max-workers 10 && \
@@ -36,9 +34,9 @@ RUN python3 -m venv /opt/venv
 COPY poetry.lock pyproject.toml ./
 RUN poetry install --sync --no-interaction --no-ansi --no-root --with ${DEVICE} --without dev

-FROM python:3.11-slim-bookworm@sha256:90f8795536170fd08236d2ceb74fe7065dbf74f738d8b84bfbf263656654dc9b as prod-cpu
+FROM python:3.11-slim-bookworm@sha256:ce81dc539f0aedc9114cae640f8352fad83d37461c24a3615b01f081d0c0583a as prod-cpu

-FROM openvino/ubuntu22_runtime:2023.3.0@sha256:176646df619032ea6c10faf842867119c393e7497b7f88b5e307e932a0fd5aa8 as prod-openvino
+FROM openvino/ubuntu22_runtime:2023.1.0@sha256:002842a9005ba01543b7169ff6f14ecbec82287f09c4d1dd37717f0a8e8754a7 as prod-openvino
 USER root

 FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04@sha256:2d913b09e6be8387e1a10976933642c73c840c0b735f0bf3c28d97fc9bc422e0 as prod-cuda
@@ -58,14 +56,14 @@ RUN apt-get update && apt-get install -y --no-install-recommends ocl-icd-libopen
    mkdir /opt/armnn

 COPY --from=builder-armnn \
-    /opt/armnn/libarmnn.so.?? \
-    /opt/armnn/libarmnnOnnxParser.so.?? \
-    /opt/armnn/libarmnnDeserializer.so.?? \
-    /opt/armnn/libarmnnTfLiteParser.so.?? \
-    /opt/armnn/libprotobuf.so.?.??.?.? \
-    /opt/ann/libann.s[o] \
-    /opt/ann/build.sh \
-    /opt/armnn/
+      /opt/armnn/libarmnn.so.?? \
+      /opt/armnn/libarmnnOnnxParser.so.?? \
+      /opt/armnn/libarmnnDeserializer.so.?? \
+      /opt/armnn/libarmnnTfLiteParser.so.?? \
+      /opt/armnn/libprotobuf.so.?.??.?.? \
+      /opt/ann/libann.s[o] \
+      /opt/ann/build.sh \
+      /opt/armnn/

 FROM prod-${DEVICE} as prod

@@ -75,12 +73,11 @@ RUN apt-get update && \

 WORKDIR /usr/src/app
 ENV NODE_ENV=production \
-    TRANSFORMERS_CACHE=/cache \
-    PYTHONDONTWRITEBYTECODE=1 \
-    PYTHONUNBUFFERED=1 \
-    PATH="/opt/venv/bin:$PATH" \
-    PYTHONPATH=/usr/src \
-    DEVICE=${DEVICE}
+  TRANSFORMERS_CACHE=/cache \
+  PYTHONDONTWRITEBYTECODE=1 \
+  PYTHONUNBUFFERED=1 \
+  PATH="/opt/venv/bin:$PATH" \
+  PYTHONPATH=/usr/src

 # prevent core dumps
 RUN echo "hard core 0" >> /etc/security/limits.conf && \
@@ -12,6 +12,8 @@ from rich.logging import RichHandler
 from uvicorn import Server
 from uvicorn.workers import UvicornWorker

+from .schemas import ModelType
+

 class PreloadModelData(BaseModel):
    clip: str | None
@@ -19,7 +21,7 @@ class PreloadModelData(BaseModel):


 class Settings(BaseSettings):
-    cache_folder: Path = Path("/cache")
+    cache_folder: str = "/cache"
    model_ttl: int = 300
    model_ttl_poll_s: int = 10
    host: str = "0.0.0.0"
@@ -53,6 +55,14 @@ def clean_name(model_name: str) -> str:
    return model_name.split("/")[-1].translate(_clean_name)


+def get_cache_dir(model_name: str, model_type: ModelType) -> Path:
+    return Path(settings.cache_folder) / model_type.value / clean_name(model_name)
+
+
+def get_hf_model_name(model_name: str) -> str:
+    return f"immich-app/{clean_name(model_name)}"
+
+
 LOG_LEVELS: dict[str, int] = {
    "critical": logging.ERROR,
    "error": logging.ERROR,
@@ -6,21 +6,22 @@ import threading
 import time
 from concurrent.futures import ThreadPoolExecutor
 from contextlib import asynccontextmanager
-from functools import partial
 from typing import Any, AsyncGenerator, Callable, Iterator
+from zipfile import BadZipFile

 import orjson
 from fastapi import Depends, FastAPI, Form, HTTPException, UploadFile
 from fastapi.responses import ORJSONResponse
+from onnxruntime.capi.onnxruntime_pybind11_state import InvalidProtobuf, NoSuchFile
 from starlette.formparsers import MultiPartParser

+from app.models.base import InferenceModel
+
 from .config import PreloadModelData, log, settings
 from .models.cache import ModelCache
 from .schemas import (
    MessageResponse,
-    ModelTask,
    ModelType,
-    Predictor,
    TextResponse,
 )

@@ -62,21 +63,12 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
        gc.collect()


-async def preload_models(preload: PreloadModelData) -> None:
-    log.info(f"Preloading models: {preload}")
-    if preload.clip is not None:
-        model = await model_cache.get(preload.clip, ModelType.TEXTUAL, ModelTask.SEARCH)
-        await load(model)
-
-        model = await model_cache.get(preload.clip, ModelType.VISUAL, ModelTask.SEARCH)
-        await load(model)
-
-    if preload.facial_recognition is not None:
-        model = await model_cache.get(preload.facial_recognition, ModelType.DETECTION, ModelTask.FACIAL_RECOGNITION)
-        await load(model)
-
-        model = await model_cache.get(preload.facial_recognition, ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION)
-        await load(model)
+async def preload_models(preload_models: PreloadModelData) -> None:
+    log.info(f"Preloading models: {preload_models}")
+    if preload_models.clip is not None:
+        await load(await model_cache.get(preload_models.clip, ModelType.CLIP))
+    if preload_models.facial_recognition is not None:
+        await load(await model_cache.get(preload_models.facial_recognition, ModelType.FACIAL_RECOGNITION))


 def update_state() -> Iterator[None]:
@@ -106,7 +98,6 @@ def ping() -> str:
 async def predict(
    model_name: str = Form(alias="modelName"),
    model_type: ModelType = Form(alias="modelType"),
-    model_task: ModelTask = Form(alias="modelTask"),
    options: str = Form(default="{}"),
    text: str | None = Form(default=None),
    image: UploadFile | None = None,
@@ -122,30 +113,39 @@ async def predict(
    except orjson.JSONDecodeError:
        raise HTTPException(400, f"Invalid options JSON: {options}")

-    model = await model_cache.get(model_name, model_type, model_task, ttl=settings.model_ttl, **kwargs)
-    model = await load(model)
-    outputs = await run(model.predict, inputs, **kwargs)
+    model = await load(await model_cache.get(model_name, model_type, ttl=settings.model_ttl, **kwargs))
+    model.configure(**kwargs)
+    outputs = await run(model.predict, inputs)
    return ORJSONResponse(outputs)


-async def run(func: Callable[..., Any], *args: Any, **kwargs: Any) -> Any:
+async def run(func: Callable[..., Any], inputs: Any) -> Any:
    if thread_pool is None:
-        return func(*args, **kwargs)
-    partial_func = partial(func, *args, **kwargs)
-    return await asyncio.get_running_loop().run_in_executor(thread_pool, partial_func)
+        return func(inputs)
+    return await asyncio.get_running_loop().run_in_executor(thread_pool, func, inputs)


-async def load(model: Predictor) -> Predictor:
+async def load(model: InferenceModel) -> InferenceModel:
    if model.loaded:
        return model

-    def _load(model: Predictor) -> Predictor:
+    def _load(model: InferenceModel) -> None:
        with lock:
            model.load()
-        return model

-    await run(_load, model)
-    return model
+    try:
+        await run(_load, model)
+        return model
+    except (OSError, InvalidProtobuf, BadZipFile, NoSuchFile):
+        log.warning(
+            (
+                f"Failed to load {model.model_type.replace('_', ' ')} model '{model.model_name}'."
+                "Clearing cache and retrying."
+            )
+        )
+        model.clear_cache()
+        await run(_load, model)
+        return model


 async def idle_shutdown_task() -> None:
@@ -1,31 +1,24 @@
 from typing import Any

-from app.models.clip.textual import MClipTextualEncoder, OpenClipTextualEncoder
-from app.models.clip.visual import OpenClipVisualEncoder
-from app.schemas import ModelSource, ModelTask, ModelType, Predictor
+from app.schemas import ModelType

-from .constants import get_model_source
-from .facial_recognition.detection import FaceDetector
-from .facial_recognition.recognition import FaceRecognizer
+from .base import InferenceModel
+from .clip import MCLIPEncoder, OpenCLIPEncoder
+from .constants import is_insightface, is_mclip, is_openclip
+from .facial_recognition import FaceRecognizer


-def from_model_type(model_name: str, model_type: ModelType, model_task: ModelTask, **model_kwargs: Any) -> Predictor:
-    source = get_model_source(model_name)
-    match source, model_type, model_task:
-        case ModelSource.OPENCLIP | ModelSource.MCLIP, ModelType.VISUAL, ModelTask.SEARCH:
-            return OpenClipVisualEncoder(model_name, **model_kwargs)
-
-        case ModelSource.OPENCLIP, ModelType.TEXTUAL, ModelTask.SEARCH:
-            return OpenClipTextualEncoder(model_name, **model_kwargs)
-
-        case ModelSource.MCLIP, ModelType.TEXTUAL, ModelTask.SEARCH:
-            return MClipTextualEncoder(model_name, **model_kwargs)
-
-        case ModelSource.INSIGHTFACE, ModelType.DETECTION, ModelTask.FACIAL_RECOGNITION:
-            return FaceDetector(model_name, **model_kwargs)
-
-        case ModelSource.INSIGHTFACE, ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION:
-            return FaceRecognizer(model_name, **model_kwargs)
-
+def from_model_type(model_type: ModelType, model_name: str, **model_kwargs: Any) -> InferenceModel:
+    match model_type:
+        case ModelType.CLIP:
+            if is_openclip(model_name):
+                return OpenCLIPEncoder(model_name, **model_kwargs)
+            elif is_mclip(model_name):
+                return MCLIPEncoder(model_name, **model_kwargs)
+        case ModelType.FACIAL_RECOGNITION:
+            if is_insightface(model_name):
+                return FaceRecognizer(model_name, **model_kwargs)
        case _:
-            raise ValueError(f"Unknown model combination: {source}, {model_type}, {model_task}")
+            raise ValueError(f"Unknown model type {model_type}")
+
+    raise ValueError(f"Unknown {model_type} model {model_name}")
@@ -1,26 +1,24 @@
 from __future__ import annotations

+import os
 from abc import ABC, abstractmethod
 from pathlib import Path
 from shutil import rmtree
-from typing import Any, ClassVar
-from zipfile import BadZipFile
+from typing import Any

 import onnxruntime as ort
-from onnxruntime.capi.onnxruntime_pybind11_state import InvalidProtobuf, NoSuchFile
 from huggingface_hub import snapshot_download

 import ann.ann
 from app.models.constants import SUPPORTED_PROVIDERS

-from ..config import clean_name, log, settings
-from ..schemas import ModelFormat, ModelSession, ModelTask, ModelType
+from ..config import get_cache_dir, get_hf_model_name, log, settings
+from ..schemas import ModelRuntime, ModelType
 from .ann import AnnSession


 class InferenceModel(ABC):
-    _model_task: ClassVar[ModelTask]
-    _model_type: ClassVar[ModelType]
+    _model_type: ModelType

    def __init__(
        self,
@@ -29,16 +27,16 @@ class InferenceModel(ABC):
        providers: list[str] | None = None,
        provider_options: list[dict[str, Any]] | None = None,
        sess_options: ort.SessionOptions | None = None,
-        preferred_format: ModelFormat | None = None,
+        preferred_runtime: ModelRuntime | None = None,
        **model_kwargs: Any,
    ) -> None:
        self.loaded = False
-        self.model_name = clean_name(model_name)
+        self.model_name = model_name
        self.cache_dir = Path(cache_dir) if cache_dir is not None else self.cache_dir_default
        self.providers = providers if providers is not None else self.providers_default
        self.provider_options = provider_options if provider_options is not None else self.provider_options_default
        self.sess_options = sess_options if sess_options is not None else self.sess_options_default
-        self.preferred_runtime = preferred_format if preferred_format is not None else self.preferred_runtime_default
+        self.preferred_runtime = preferred_runtime if preferred_runtime is not None else self.preferred_runtime_default

    def download(self) -> None:
        if not self.cached:
@@ -50,47 +48,35 @@ class InferenceModel(ABC):
    def load(self) -> None:
        if self.loaded:
            return
-
-        try:
-            self.download()
-            log.info(f"Loading {self.model_type.replace('-', ' ')} model '{self.model_name}' to memory")
-            self.session = self._load()
-        except (OSError, InvalidProtobuf, BadZipFile, NoSuchFile):
-            log.warning(
-                (
-                    f"Failed to load {self.model_type.replace('_', ' ')} model '{self.model_name}'."
-                    "Clearing cache and retrying."
-                )
-            )
-            self.clear_cache()
-            self.download()
-            self.session = self._load()
+        self.download()
+        log.info(f"Loading {self.model_type.replace('-', ' ')} model '{self.model_name}' to memory")
+        self._load()
        self.loaded = True

    def predict(self, inputs: Any, **model_kwargs: Any) -> Any:
        self.load()
        if model_kwargs:
            self.configure(**model_kwargs)
-        return self._predict(inputs, **model_kwargs)
+        return self._predict(inputs)

    @abstractmethod
-    def _predict(self, inputs: Any, **model_kwargs: Any) -> Any: ...
+    def _predict(self, inputs: Any) -> Any: ...

-    def configure(self, **kwargs: Any) -> None:
+    def configure(self, **model_kwargs: Any) -> None:
        pass

    def _download(self) -> None:
-        ignore_patterns = [] if self.preferred_runtime == ModelFormat.ARMNN else ["*.armnn"]
+        ignore_patterns = [] if self.preferred_runtime == ModelRuntime.ARMNN else ["*.armnn"]
        snapshot_download(
-            f"immich-app/{clean_name(self.model_name)}",
+            get_hf_model_name(self.model_name),
            cache_dir=self.cache_dir,
            local_dir=self.cache_dir,
            local_dir_use_symlinks=False,
            ignore_patterns=ignore_patterns,
        )

-    def _load(self) -> ModelSession:
-        return self._make_session(self.model_path)
+    @abstractmethod
+    def _load(self) -> None: ...

    def clear_cache(self) -> None:
        if not self.cache_dir.exists():
@@ -114,7 +100,7 @@ class InferenceModel(ABC):
            self.cache_dir.unlink()
        self.cache_dir.mkdir(parents=True, exist_ok=True)

-    def _make_session(self, model_path: Path) -> ModelSession:
+    def _make_session(self, model_path: Path) -> AnnSession | ort.InferenceSession:
        if not model_path.is_file():
            onnx_path = model_path.with_suffix(".onnx")
            if not onnx_path.is_file():
@@ -129,24 +115,21 @@ class InferenceModel(ABC):
            case ".armnn":
                session = AnnSession(model_path)
            case ".onnx":
-                session = ort.InferenceSession(
-                    model_path.as_posix(),
-                    sess_options=self.sess_options,
-                    providers=self.providers,
-                    provider_options=self.provider_options,
-                )
+                cwd = os.getcwd()
+                try:
+                    os.chdir(model_path.parent)
+                    session = ort.InferenceSession(
+                        model_path.as_posix(),
+                        sess_options=self.sess_options,
+                        providers=self.providers,
+                        provider_options=self.provider_options,
+                    )
+                finally:
+                    os.chdir(cwd)
            case _:
                raise ValueError(f"Unsupported model file type: {model_path.suffix}")
        return session

-    @property
-    def model_path(self) -> Path:
-        return self.cache_dir / self.model_type.value / f"model.{self.preferred_runtime}"
-
-    @property
-    def model_task(self) -> ModelTask:
-        return self._model_task
-
    @property
    def model_type(self) -> ModelType:
        return self._model_type
@@ -161,11 +144,11 @@ class InferenceModel(ABC):

    @property
    def cache_dir_default(self) -> Path:
-        return settings.cache_folder / self.model_task.value / self.model_name
+        return get_cache_dir(self.model_name, self.model_type)

    @property
    def cached(self) -> bool:
-        return self.model_path.is_file()
+        return self.cache_dir.is_dir() and any(self.cache_dir.iterdir())

    @property
    def providers(self) -> list[str]:
@@ -209,7 +192,7 @@ class InferenceModel(ABC):
                case "CPUExecutionProvider" | "CUDAExecutionProvider":
                    option = {"arena_extend_strategy": "kSameAsRequested"}
                case "OpenVINOExecutionProvider":
-                    option = {"device_type": "GPU_FP32", "cache_dir": (self.cache_dir / "openvino").as_posix()}
+                    option = {"device_type": "GPU_FP32"}
                case _:
                    option = {}
            options.append(option)
@@ -249,14 +232,14 @@ class InferenceModel(ABC):
        return sess_options

    @property
-    def preferred_runtime(self) -> ModelFormat:
+    def preferred_runtime(self) -> ModelRuntime:
        return self._preferred_runtime

    @preferred_runtime.setter
-    def preferred_runtime(self, preferred_runtime: ModelFormat) -> None:
+    def preferred_runtime(self, preferred_runtime: ModelRuntime) -> None:
        log.debug(f"Setting preferred runtime to {preferred_runtime}")
        self._preferred_runtime = preferred_runtime

    @property
-    def preferred_runtime_default(self) -> ModelFormat:
-        return ModelFormat.ARMNN if ann.ann.is_available and settings.ann else ModelFormat.ONNX
+    def preferred_runtime_default(self) -> ModelRuntime:
+        return ModelRuntime.ARMNN if ann.ann.is_available and settings.ann else ModelRuntime.ONNX
@@ -5,9 +5,9 @@ from aiocache.lock import OptimisticLock
 from aiocache.plugins import TimingPlugin

 from app.models import from_model_type
-from app.models.facial_recognition.pipeline import FacialRecognitionPipeline

-from ..schemas import ModelTask, ModelType, Predictor, has_profiling
+from ..schemas import ModelType, has_profiling
+from .base import InferenceModel


 class ModelCache:
@@ -31,13 +31,11 @@ class ModelCache:
        if profiling:
            plugins.append(TimingPlugin())

-        self.should_revalidate = revalidate
+        self.revalidate_enable = revalidate

        self.cache = SimpleMemoryCache(timeout=timeout, plugins=plugins, namespace=None)

-    async def get(
-        self, model_name: str, model_type: ModelType, model_task: ModelTask, **model_kwargs: Any
-    ) -> Predictor:
+    async def get(self, model_name: str, model_type: ModelType, **model_kwargs: Any) -> InferenceModel:
        """
        Args:
            model_name: Name of model in the model hub used for the task.
@@ -47,38 +45,17 @@ class ModelCache:
            model: The requested model.
        """

-        key = f"{model_name}{model_type.value}{model_task.value}"
+        key = f"{model_name}{model_type.value}{model_kwargs.get('mode', '')}"

        async with OptimisticLock(self.cache, key) as lock:
-            model: Predictor | None = await self.cache.get(key)
+            model: InferenceModel | None = await self.cache.get(key)
            if model is None:
-                if model_type == ModelType.PIPELINE:
-                    model = await self._get_pipeline(model_name, model_task, **model_kwargs)
-                else:
-                    model = from_model_type(model_name, model_type, model_task, **model_kwargs)
+                model = from_model_type(model_type, model_name, **model_kwargs)
                await lock.cas(model, ttl=model_kwargs.get("ttl", None))
-            elif self.should_revalidate:
+            elif self.revalidate_enable:
                await self.revalidate(key, model_kwargs.get("ttl", None))
        return model

-    async def _get_pipeline(self, model_name: str, model_task: ModelTask, **model_kwargs: Any) -> Predictor:
-        """
-        Args:
-            model_name: Name of model in the model hub used for the task.
-            model_type: Model type or task, which determines which model zoo is used.
-
-        Returns:
-            model: The requested model.
-        """
-        match model_task:
-            case ModelTask.FACIAL_RECOGNITION:
-                det_model: Any = await self.get(model_name, ModelType.DETECTION, model_task, **model_kwargs)
-                rec_model: Any = await self.get(model_name, ModelType.RECOGNITION, model_task, **model_kwargs)
-                return FacialRecognitionPipeline(det_model, rec_model)
-
-            case _:
-                raise ValueError(f"Unknown model task: {model_task}")
-
    async def get_profiling(self) -> dict[str, float] | None:
        if not has_profiling(self.cache):
            return None
@@ -0,0 +1,189 @@
+import json
+from abc import abstractmethod
+from functools import cached_property
+from io import BytesIO
+from pathlib import Path
+from typing import Any, Literal
+
+import numpy as np
+from numpy.typing import NDArray
+from PIL import Image
+from tokenizers import Encoding, Tokenizer
+
+from app.config import clean_name, log
+from app.models.transforms import crop, get_pil_resampling, normalize, resize, to_numpy
+from app.schemas import ModelType
+
+from .base import InferenceModel
+
+
+class BaseCLIPEncoder(InferenceModel):
+    _model_type = ModelType.CLIP
+
+    def __init__(
+        self,
+        model_name: str,
+        cache_dir: Path | str | None = None,
+        mode: Literal["text", "vision"] | None = None,
+        **model_kwargs: Any,
+    ) -> None:
+        self.mode = mode
+        super().__init__(model_name, cache_dir, **model_kwargs)
+
+    def _load(self) -> None:
+        if self.mode == "text" or self.mode is None:
+            log.debug(f"Loading clip text model '{self.model_name}'")
+            self.text_model = self._make_session(self.textual_path)
+            log.debug(f"Loaded clip text model '{self.model_name}'")
+
+        if self.mode == "vision" or self.mode is None:
+            log.debug(f"Loading clip vision model '{self.model_name}'")
+            self.vision_model = self._make_session(self.visual_path)
+            log.debug(f"Loaded clip vision model '{self.model_name}'")
+
+    def _predict(self, image_or_text: Image.Image | str) -> NDArray[np.float32]:
+        if isinstance(image_or_text, bytes):
+            image_or_text = Image.open(BytesIO(image_or_text))
+
+        match image_or_text:
+            case Image.Image():
+                if self.mode == "text":
+                    raise TypeError("Cannot encode image as text-only model")
+                outputs: NDArray[np.float32] = self.vision_model.run(None, self.transform(image_or_text))[0][0]
+            case str():
+                if self.mode == "vision":
+                    raise TypeError("Cannot encode text as vision-only model")
+                outputs = self.text_model.run(None, self.tokenize(image_or_text))[0][0]
+            case _:
+                raise TypeError(f"Expected Image or str, but got: {type(image_or_text)}")
+
+        return outputs
+
+    @abstractmethod
+    def tokenize(self, text: str) -> dict[str, NDArray[np.int32]]:
+        pass
+
+    @abstractmethod
+    def transform(self, image: Image.Image) -> dict[str, NDArray[np.float32]]:
+        pass
+
+    @property
+    def textual_dir(self) -> Path:
+        return self.cache_dir / "textual"
+
+    @property
+    def visual_dir(self) -> Path:
+        return self.cache_dir / "visual"
+
+    @property
+    def model_cfg_path(self) -> Path:
+        return self.cache_dir / "config.json"
+
+    @property
+    def textual_path(self) -> Path:
+        return self.textual_dir / f"model.{self.preferred_runtime}"
+
+    @property
+    def visual_path(self) -> Path:
+        return self.visual_dir / f"model.{self.preferred_runtime}"
+
+    @property
+    def tokenizer_file_path(self) -> Path:
+        return self.textual_dir / "tokenizer.json"
+
+    @property
+    def tokenizer_cfg_path(self) -> Path:
+        return self.textual_dir / "tokenizer_config.json"
+
+    @property
+    def preprocess_cfg_path(self) -> Path:
+        return self.visual_dir / "preprocess_cfg.json"
+
+    @property
+    def cached(self) -> bool:
+        return self.textual_path.is_file() and self.visual_path.is_file()
+
+    @cached_property
+    def model_cfg(self) -> dict[str, Any]:
+        log.debug(f"Loading model config for CLIP model '{self.model_name}'")
+        model_cfg: dict[str, Any] = json.load(self.model_cfg_path.open())
+        log.debug(f"Loaded model config for CLIP model '{self.model_name}'")
+        return model_cfg
+
+    @cached_property
+    def tokenizer_file(self) -> dict[str, Any]:
+        log.debug(f"Loading tokenizer file for CLIP model '{self.model_name}'")
+        tokenizer_file: dict[str, Any] = json.load(self.tokenizer_file_path.open())
+        log.debug(f"Loaded tokenizer file for CLIP model '{self.model_name}'")
+        return tokenizer_file
+
+    @cached_property
+    def tokenizer_cfg(self) -> dict[str, Any]:
+        log.debug(f"Loading tokenizer config for CLIP model '{self.model_name}'")
+        tokenizer_cfg: dict[str, Any] = json.load(self.tokenizer_cfg_path.open())
+        log.debug(f"Loaded tokenizer config for CLIP model '{self.model_name}'")
+        return tokenizer_cfg
+
+    @cached_property
+    def preprocess_cfg(self) -> dict[str, Any]:
+        log.debug(f"Loading visual preprocessing config for CLIP model '{self.model_name}'")
+        preprocess_cfg: dict[str, Any] = json.load(self.preprocess_cfg_path.open())
+        log.debug(f"Loaded visual preprocessing config for CLIP model '{self.model_name}'")
+        return preprocess_cfg
+
+
+class OpenCLIPEncoder(BaseCLIPEncoder):
+    def __init__(
+        self,
+        model_name: str,
+        cache_dir: Path | str | None = None,
+        mode: Literal["text", "vision"] | None = None,
+        **model_kwargs: Any,
+    ) -> None:
+        super().__init__(clean_name(model_name), cache_dir, mode, **model_kwargs)
+
+    def _load(self) -> None:
+        super()._load()
+        self._load_tokenizer()
+
+        size: list[int] | int = self.preprocess_cfg["size"]
+        self.size = size[0] if isinstance(size, list) else size
+
+        self.resampling = get_pil_resampling(self.preprocess_cfg["interpolation"])
+        self.mean = np.array(self.preprocess_cfg["mean"], dtype=np.float32)
+        self.std = np.array(self.preprocess_cfg["std"], dtype=np.float32)
+
+    def _load_tokenizer(self) -> Tokenizer:
+        log.debug(f"Loading tokenizer for CLIP model '{self.model_name}'")
+
+        text_cfg: dict[str, Any] = self.model_cfg["text_cfg"]
+        context_length: int = text_cfg.get("context_length", 77)
+        pad_token: str = self.tokenizer_cfg["pad_token"]
+
+        self.tokenizer: Tokenizer = Tokenizer.from_file(self.tokenizer_file_path.as_posix())
+
+        pad_id: int = self.tokenizer.token_to_id(pad_token)
+        self.tokenizer.enable_padding(length=context_length, pad_token=pad_token, pad_id=pad_id)
+        self.tokenizer.enable_truncation(max_length=context_length)
+
+        log.debug(f"Loaded tokenizer for CLIP model '{self.model_name}'")
+
+    def tokenize(self, text: str) -> dict[str, NDArray[np.int32]]:
+        tokens: Encoding = self.tokenizer.encode(text)
+        return {"text": np.array([tokens.ids], dtype=np.int32)}
+
+    def transform(self, image: Image.Image) -> dict[str, NDArray[np.float32]]:
+        image = resize(image, self.size)
+        image = crop(image, self.size)
+        image_np = to_numpy(image)
+        image_np = normalize(image_np, self.mean, self.std)
+        return {"image": np.expand_dims(image_np.transpose(2, 0, 1), 0)}
+
+
+class MCLIPEncoder(OpenCLIPEncoder):
+    def tokenize(self, text: str) -> dict[str, NDArray[np.int32]]:
+        tokens: Encoding = self.tokenizer.encode(text)
+        return {
+            "input_ids": np.array([tokens.ids], dtype=np.int32),
+            "attention_mask": np.array([tokens.attention_mask], dtype=np.int32),
+        }
@@ -1,111 +0,0 @@
-import json
-from abc import abstractmethod
-from functools import cached_property
-from pathlib import Path
-from typing import Any
-
-import numpy as np
-from numpy.typing import NDArray
-from tokenizers import Encoding, Tokenizer
-
-from app.config import log
-from app.schemas import ModelSession, ModelTask, ModelType
-
-from app.models.base import InferenceModel
-
-
-class BaseCLIPTextualEncoder(InferenceModel):
-    _model_task = ModelTask.SEARCH
-    _model_type = ModelType.TEXTUAL
-
-    def _predict(self, inputs: str, **kwargs: Any) -> NDArray[np.float32]:
-        res: NDArray[np.float32] = self.session.run(None, self.tokenize(inputs))[0][0]
-        return res
-
-    def _load(self) -> ModelSession:
-        log.debug(f"Loading tokenizer for CLIP model '{self.model_name}'")
-        self.tokenizer = self._load_tokenizer()
-        log.debug(f"Loaded tokenizer for CLIP model '{self.model_name}'")
-
-        return super()._load()
-
-    @abstractmethod
-    def _load_tokenizer(self) -> Tokenizer:
-        pass
-
-    @abstractmethod
-    def tokenize(self, text: str) -> dict[str, NDArray[np.int32]]:
-        pass
-
-    @property
-    def model_dir(self) -> Path:
-        return self.cache_dir / "textual"
-
-    @property
-    def model_cfg_path(self) -> Path:
-        return self.cache_dir / "config.json"
-
-    @property
-    def model_path(self) -> Path:
-        return self.model_dir / f"model.{self.preferred_runtime}"
-
-    @property
-    def tokenizer_file_path(self) -> Path:
-        return self.model_dir / "tokenizer.json"
-
-    @property
-    def tokenizer_cfg_path(self) -> Path:
-        return self.model_dir / "tokenizer_config.json"
-
-    @property
-    def cached(self) -> bool:
-        return self.model_path.is_file()
-
-    @cached_property
-    def model_cfg(self) -> dict[str, Any]:
-        log.debug(f"Loading model config for CLIP model '{self.model_name}'")
-        model_cfg: dict[str, Any] = json.load(self.model_cfg_path.open())
-        log.debug(f"Loaded model config for CLIP model '{self.model_name}'")
-        return model_cfg
-
-    @cached_property
-    def tokenizer_file(self) -> dict[str, Any]:
-        log.debug(f"Loading tokenizer file for CLIP model '{self.model_name}'")
-        tokenizer_file: dict[str, Any] = json.load(self.tokenizer_file_path.open())
-        log.debug(f"Loaded tokenizer file for CLIP model '{self.model_name}'")
-        return tokenizer_file
-
-    @cached_property
-    def tokenizer_cfg(self) -> dict[str, Any]:
-        log.debug(f"Loading tokenizer config for CLIP model '{self.model_name}'")
-        tokenizer_cfg: dict[str, Any] = json.load(self.tokenizer_cfg_path.open())
-        log.debug(f"Loaded tokenizer config for CLIP model '{self.model_name}'")
-        return tokenizer_cfg
-
-
-class OpenClipTextualEncoder(BaseCLIPTextualEncoder):
-    def _load_tokenizer(self) -> Tokenizer:
-        text_cfg: dict[str, Any] = self.model_cfg["text_cfg"]
-        context_length: int = text_cfg.get("context_length", 77)
-        pad_token: str = self.tokenizer_cfg["pad_token"]
-
-        tokenizer: Tokenizer = Tokenizer.from_file(self.tokenizer_file_path.as_posix())
-
-        pad_id: int = tokenizer.token_to_id(pad_token)
-        tokenizer.enable_padding(length=context_length, pad_token=pad_token, pad_id=pad_id)
-        tokenizer.enable_truncation(max_length=context_length)
-
-        return tokenizer
-
-    def tokenize(self, text: str) -> dict[str, NDArray[np.int32]]:
-        tokens: Encoding = self.tokenizer.encode(text)
-        return {"text": np.array([tokens.ids], dtype=np.int32)}
-
-
-class MClipTextualEncoder(OpenClipTextualEncoder):
-    def tokenize(self, text: str) -> dict[str, NDArray[np.int32]]:
-        tokens: Encoding = self.tokenizer.encode(text)
-        return {
-            "input_ids": np.array([tokens.ids], dtype=np.int32),
-            "attention_mask": np.array([tokens.attention_mask], dtype=np.int32),
-        }
@@ -1,84 +0,0 @@
-import json
-from abc import abstractmethod
-from functools import cached_property
-from io import BytesIO
-from pathlib import Path
-from typing import Any
-
-import numpy as np
-from numpy.typing import NDArray
-from PIL import Image
-
-from app.config import log
-from app.models.transforms import crop_pil, get_pil_resampling, normalize, resize_pil, to_numpy
-from app.schemas import ModelSession, ModelTask, ModelType
-
-from app.models.base import InferenceModel
-
-
-class BaseCLIPVisualEncoder(InferenceModel):
-    _model_task = ModelTask.SEARCH
-    _model_type = ModelType.VISUAL
-
-    def _predict(self, inputs: Image.Image | bytes, **kwargs: Any) -> NDArray[np.float32]:
-        if isinstance(inputs, bytes):
-            inputs = Image.open(BytesIO(inputs))
-        res: NDArray[np.float32] = self.session.run(None, self.transform(inputs))[0][0]
-        return res
-
-    @abstractmethod
-    def transform(self, image: Image.Image) -> dict[str, NDArray[np.float32]]:
-        pass
-
-    @property
-    def model_dir(self) -> Path:
-        return self.cache_dir / "visual"
-
-    @property
-    def model_cfg_path(self) -> Path:
-        return self.cache_dir / "config.json"
-
-    @property
-    def model_path(self) -> Path:
-        return self.model_dir / f"model.{self.preferred_runtime}"
-
-    @property
-    def preprocess_cfg_path(self) -> Path:
-        return self.model_dir / "preprocess_cfg.json"
-
-    @property
-    def cached(self) -> bool:
-        return self.model_path.is_file()
-
-    @cached_property
-    def model_cfg(self) -> dict[str, Any]:
-        log.debug(f"Loading model config for CLIP model '{self.model_name}'")
-        model_cfg: dict[str, Any] = json.load(self.model_cfg_path.open())
-        log.debug(f"Loaded model config for CLIP model '{self.model_name}'")
-        return model_cfg
-
-    @cached_property
-    def preprocess_cfg(self) -> dict[str, Any]:
-        log.debug(f"Loading visual preprocessing config for CLIP model '{self.model_name}'")
-        preprocess_cfg: dict[str, Any] = json.load(self.preprocess_cfg_path.open())
-        log.debug(f"Loaded visual preprocessing config for CLIP model '{self.model_name}'")
-        return preprocess_cfg
-
-
-class OpenClipVisualEncoder(BaseCLIPVisualEncoder):
-    def _load(self) -> ModelSession:
-        size: list[int] | int = self.preprocess_cfg["size"]
-        self.size = size[0] if isinstance(size, list) else size
-
-        self.resampling = get_pil_resampling(self.preprocess_cfg["interpolation"])
-        self.mean = np.array(self.preprocess_cfg["mean"], dtype=np.float32)
-        self.std = np.array(self.preprocess_cfg["std"], dtype=np.float32)
-
-        return super()._load()
-
-    def transform(self, image: Image.Image) -> dict[str, NDArray[np.float32]]:
-        image = resize_pil(image, self.size)
-        image = crop_pil(image, self.size)
-        image_np = to_numpy(image)
-        image_np = normalize(image_np, self.mean, self.std)
-        return {"image": np.expand_dims(image_np.transpose(2, 0, 1), 0)}
@@ -1,5 +1,4 @@
 from app.config import clean_name
-from app.schemas import ModelSource

 _OPENCLIP_MODELS = {
    "RN50__openai",
@@ -55,16 +54,13 @@ _INSIGHTFACE_MODELS = {
 SUPPORTED_PROVIDERS = ["CUDAExecutionProvider", "OpenVINOExecutionProvider", "CPUExecutionProvider"]


-def get_model_source(model_name: str) -> ModelSource | None:
-    cleaned_name = clean_name(model_name)
+def is_openclip(model_name: str) -> bool:
+    return clean_name(model_name) in _OPENCLIP_MODELS

-    if cleaned_name in _INSIGHTFACE_MODELS:
-        return ModelSource.INSIGHTFACE

-    if cleaned_name in _MCLIP_MODELS:
-        return ModelSource.MCLIP
+def is_mclip(model_name: str) -> bool:
+    return clean_name(model_name) in _MCLIP_MODELS

-    if cleaned_name in _OPENCLIP_MODELS:
-        return ModelSource.OPENCLIP

-    return None
+def is_insightface(model_name: str) -> bool:
+    return clean_name(model_name) in _INSIGHTFACE_MODELS
@@ -0,0 +1,90 @@
+from pathlib import Path
+from typing import Any
+
+import cv2
+import numpy as np
+from insightface.model_zoo import ArcFaceONNX, RetinaFace
+from insightface.utils.face_align import norm_crop
+from numpy.typing import NDArray
+
+from app.config import clean_name
+from app.schemas import Face, ModelType, is_ndarray
+
+from .base import InferenceModel
+
+
+class FaceRecognizer(InferenceModel):
+    _model_type = ModelType.FACIAL_RECOGNITION
+
+    def __init__(
+        self,
+        model_name: str,
+        min_score: float = 0.7,
+        cache_dir: Path | str | None = None,
+        **model_kwargs: Any,
+    ) -> None:
+        self.min_score = model_kwargs.pop("minScore", min_score)
+        super().__init__(clean_name(model_name), cache_dir, **model_kwargs)
+
+    def _load(self) -> None:
+        self.det_model = RetinaFace(session=self._make_session(self.det_file))
+        self.rec_model = ArcFaceONNX(
+            self.rec_file.with_suffix(".onnx").as_posix(),
+            session=self._make_session(self.rec_file),
+        )
+
+        self.det_model.prepare(
+            ctx_id=0,
+            det_thresh=self.min_score,
+            input_size=(640, 640),
+        )
+        self.rec_model.prepare(ctx_id=0)
+
+    def _predict(self, image: NDArray[np.uint8] | bytes) -> list[Face]:
+        if isinstance(image, bytes):
+            decoded_image = cv2.imdecode(np.frombuffer(image, np.uint8), cv2.IMREAD_COLOR)
+        else:
+            decoded_image = image
+        assert is_ndarray(decoded_image, np.uint8)
+        bboxes, kpss = self.det_model.detect(decoded_image)
+        if bboxes.size == 0:
+            return []
+        assert is_ndarray(kpss, np.float32)
+
+        scores = bboxes[:, 4].tolist()
+        bboxes = bboxes[:, :4].round().tolist()
+
+        results = []
+        height, width, _ = decoded_image.shape
+        for (x1, y1, x2, y2), score, kps in zip(bboxes, scores, kpss):
+            cropped_img = norm_crop(decoded_image, kps)
+            embedding: NDArray[np.float32] = self.rec_model.get_feat(cropped_img)[0]
+            face: Face = {
+                "imageWidth": width,
+                "imageHeight": height,
+                "boundingBox": {
+                    "x1": x1,
+                    "y1": y1,
+                    "x2": x2,
+                    "y2": y2,
+                },
+                "score": score,
+                "embedding": embedding,
+            }
+            results.append(face)
+        return results
+
+    @property
+    def cached(self) -> bool:
+        return self.det_file.is_file() and self.rec_file.is_file()
+
+    @property
+    def det_file(self) -> Path:
+        return self.cache_dir / "detection" / f"model.{self.preferred_runtime}"
+
+    @property
+    def rec_file(self) -> Path:
+        return self.cache_dir / "recognition" / f"model.{self.preferred_runtime}"
+
+    def configure(self, **model_kwargs: Any) -> None:
+        self.det_model.det_thresh = model_kwargs.pop("minScore", self.det_model.det_thresh)
@@ -1,60 +0,0 @@
-from pathlib import Path
-from typing import Any
-
-import cv2
-import numpy as np
-from insightface.model_zoo import RetinaFace
-from numpy.typing import NDArray
-
-from app.schemas import DetectedFace, ModelSession, ModelTask, ModelType, is_ndarray
-
-from app.models.base import InferenceModel
-
-
-class FaceDetector(InferenceModel):
-    _model_task = ModelTask.FACIAL_RECOGNITION
-    _model_type = ModelType.DETECTION
-
-    def __init__(
-        self,
-        model_name: str,
-        min_score: float = 0.7,
-        cache_dir: Path | str | None = None,
-        **model_kwargs: Any,
-    ) -> None:
-        self.min_score = model_kwargs.pop("minScore", min_score)
-        super().__init__(model_name, cache_dir, **model_kwargs)
-
-    def _load(self) -> ModelSession:
-        session = self._make_session(self.model_path)
-        self.det_model = RetinaFace(session=session)
-        self.det_model.prepare(ctx_id=0, det_thresh=self.min_score, input_size=(640, 640))
-
-        return session
-
-    def _predict(self, inputs: NDArray[np.uint8] | bytes, **kwargs: Any) -> list[DetectedFace]:
-        if isinstance(inputs, bytes):
-            decoded_image = cv2.imdecode(np.frombuffer(inputs, np.uint8), cv2.IMREAD_COLOR)
-        else:
-            decoded_image = inputs
-        assert is_ndarray(decoded_image, np.uint8)
-
-        bboxes, landmarks = self.det_model.detect(decoded_image)
-        assert is_ndarray(bboxes, np.float32)
-        assert is_ndarray(landmarks, np.float32)
-
-        if bboxes.size == 0:
-            return []
-
-        scores: list[float] = bboxes[:, 4].tolist()
-        bboxes_list: list[list[int]] = bboxes[:, :4].round().tolist()
-
-        results: list[DetectedFace] = [
-            {"box": {"x1": x1, "y1": y1, "x2": x2, "y2": y2}, "score": score, "landmarks": face_landmarks}
-            for (x1, y1, x2, y2), score, face_landmarks in zip(bboxes_list, scores, landmarks)
-        ]
-
-        return results
-
-    def configure(self, **kwargs: Any) -> None:
-        self.det_model.det_thresh = kwargs.pop("minScore", self.det_model.det_thresh)
@@ -1,31 +0,0 @@
-from typing import Any
-import cv2
-import numpy as np
-from numpy.typing import NDArray
-
-from app.models.facial_recognition.detection import FaceDetector
-from app.models.facial_recognition.recognition import FaceRecognizer
-from app.schemas import RecognizedFace, is_ndarray
-
-
-class FacialRecognitionPipeline:
-    def __init__(self, det_model: FaceDetector, rec_model: FaceRecognizer) -> None:
-        self.det_model = det_model
-        self.rec_model = rec_model
-        self.loaded = False
-
-    def load(self) -> None:
-        self.det_model.load()
-        self.rec_model.load()
-        self.loaded = True
-
-    def predict(self, inputs: NDArray[np.uint8] | bytes, **kwargs: Any) -> list[RecognizedFace]:
-        if isinstance(inputs, bytes):
-            decoded_image = cv2.imdecode(np.frombuffer(inputs, np.uint8), cv2.IMREAD_COLOR)
-        else:
-            decoded_image = inputs
-        assert is_ndarray(decoded_image, np.uint8)
-
-        faces = self.det_model.predict(decoded_image, **kwargs)
-        results: list[RecognizedFace] = self.rec_model.predict(decoded_image, faces=faces, **kwargs)
-        return results
@@ -1,65 +0,0 @@
-from pathlib import Path
-from typing import Any
-
-import cv2
-import numpy as np
-from insightface.model_zoo import ArcFaceONNX
-from insightface.utils.face_align import norm_crop
-from numpy.typing import NDArray
-
-from app.config import clean_name
-from app.models.transforms import crop_np, crop_bounding_box, resize_np
-from app.schemas import DetectedFace, ModelTask, RecognizedFace, ModelSession, ModelType, is_ndarray
-
-from ..base import InferenceModel
-
-
-class FaceRecognizer(InferenceModel):
-    _model_task = ModelTask.FACIAL_RECOGNITION
-    _model_type = ModelType.RECOGNITION
-
-    def __init__(
-        self,
-        model_name: str,
-        min_score: float = 0.7,
-        cache_dir: Path | str | None = None,
-        **model_kwargs: Any,
-    ) -> None:
-        self.min_score = model_kwargs.pop("minScore", min_score)
-        super().__init__(clean_name(model_name), cache_dir, **model_kwargs)
-
-    def _load(self) -> ModelSession:
-        session = self._make_session(self.model_path)
-        self.model = ArcFaceONNX(
-            self.model_path.with_suffix(".onnx").as_posix(),
-            session=session,
-        )
-        return session
-
-    # def _predict(self, img: Any, **kwargs: Any) -> Any:
-    def _predict(
-        self, inputs: NDArray[np.uint8] | bytes, faces: list[DetectedFace] = [], **kwargs: Any
-    ) -> list[RecognizedFace]:
-        if isinstance(inputs, bytes):
-            decoded_image = cv2.imdecode(np.frombuffer(inputs, np.uint8), cv2.IMREAD_COLOR)
-        else:
-            decoded_image = inputs
-        assert is_ndarray(decoded_image, np.float32)
-
-        results: list[RecognizedFace] = []
-        for detected_face in faces:
-            landmarks = detected_face.get("landmarks", None)
-            if landmarks is not None:
-                cropped_img = norm_crop(decoded_image, np.asarray(landmarks))
-            else:
-                cropped_img = crop_bounding_box(decoded_image, detected_face["box"])
-                cropped_img = crop_np(resize_np(cropped_img, 112), 112)
-            assert is_ndarray(cropped_img, np.uint8)
-
-            embedding = self.model.get_feat(cropped_img)[0]
-            assert is_ndarray(embedding, np.float32)
-
-            face: RecognizedFace = {"box": detected_face["box"], "embedding": embedding}
-            results.append(face)
-
-        return results
@@ -1,54 +1,19 @@
-import cv2
 import numpy as np
 from numpy.typing import NDArray
 from PIL import Image

-from app.schemas import BoundingBox, is_ndarray
-
 _PIL_RESAMPLING_METHODS = {resampling.name.lower(): resampling for resampling in Image.Resampling}


-def resize_pil(img: Image.Image, size: int) -> Image.Image:
+def resize(img: Image.Image, size: int) -> Image.Image:
    if img.width < img.height:
        return img.resize((size, int((img.height / img.width) * size)), resample=Image.BICUBIC)
    else:
        return img.resize((int((img.width / img.height) * size), size), resample=Image.BICUBIC)


-def resize_np(img: NDArray[np.float32], size: int) -> NDArray[np.float32]:
-    height, width = img.shape[:2]
-    if width < height:
-        res = cv2.resize(img, (size, int((height / width) * size)), interpolation=cv2.INTER_CUBIC)
-    else:
-        res = cv2.resize(img, (int((width / height) * size), size), interpolation=cv2.INTER_CUBIC)
-    assert is_ndarray(res, np.float32)
-    return res
-
-
-# ported from server
-def crop_bounding_box(image: NDArray[np.float32], bbox: BoundingBox, scale: float = 1.0) -> NDArray[np.float32]:
-    middle_x = (bbox["x1"] + bbox["x2"]) // 2
-    middle_y = (bbox["y1"] + bbox["y2"]) // 2
-
-    target_half_size = int(max((bbox["x2"] - bbox["x1"]) / 2, (bbox["y2"] - bbox["y1"]) / 2) * scale)
-
-    new_half_size = min(
-        middle_x - max(0, middle_x - target_half_size),
-        middle_y - max(0, middle_y - target_half_size),
-        min(image.shape[1] - 1, middle_x + target_half_size) - middle_x,
-        min(image.shape[0] - 1, middle_y + target_half_size) - middle_y,
-    )
-
-    left = middle_x - new_half_size
-    top = middle_y - new_half_size
-    width = int(new_half_size * 2)
-    height = int(new_half_size * 2)
-
-    return image[top : top + height, left : left + width]
-
-
 # https://stackoverflow.com/a/60883103
-def crop_pil(img: Image.Image, size: int) -> Image.Image:
+def crop(img: Image.Image, size: int) -> Image.Image:
    left = int((img.size[0] / 2) - (size / 2))
    upper = int((img.size[1] / 2) - (size / 2))
    right = left + size
@@ -57,16 +22,6 @@ def crop_pil(img: Image.Image, size: int) -> Image.Image:
    return img.crop((left, upper, right, lower))


-def crop_np(img: NDArray[np.float32], size: int) -> NDArray[np.generic]:
-    height, width = img.shape[:2]
-    left = int((width / 2) - (size / 2))
-    upper = int((height / 2) - (size / 2))
-    right = left + size
-    lower = upper + size
-
-    return img[upper:lower, left:right]
-
-
 def to_numpy(img: Image.Image) -> NDArray[np.float32]:
    return np.asarray(img.convert("RGB")).astype(np.float32) / 255.0

@@ -3,7 +3,7 @@ from typing import Any, Protocol, TypedDict, TypeGuard

 import numpy as np
 import numpy.typing as npt
-from pydantic import BaseModel, Field
+from pydantic import BaseModel


 class StrEnum(str, Enum):
@@ -28,60 +28,26 @@ class BoundingBox(TypedDict):
    y2: int


-class ModelTask(StrEnum):
-    FACIAL_RECOGNITION = "facial-recognition"
-    SEARCH = "clip"
-
-
 class ModelType(StrEnum):
-    DETECTION = "detection"
-    PIPELINE = "pipeline"
-    RECOGNITION = "recognition"
-    TEXTUAL = "textual"
-    VISUAL = "visual"
+    CLIP = "clip"
+    FACIAL_RECOGNITION = "facial-recognition"


-class ModelFormat(StrEnum):
-    ARMNN = "armnn"
+class ModelRuntime(StrEnum):
    ONNX = "onnx"
-
-
-class ModelSource(StrEnum):
-    INSIGHTFACE = "insightface"
-    MCLIP = "mclip"
-    OPENCLIP = "openclip"
-
-
-class ModelSession(Protocol):
-    def run(
-        self,
-        output_names: list[str] | None,
-        input_feed: dict[str, npt.NDArray[np.float32]] | dict[str, npt.NDArray[np.int32]],
-        run_options: Any = None,
-    ) -> list[npt.NDArray[np.float32]]: ...
-
-
-class Predictor(Protocol):
-    loaded: bool
-
-    def load(self) -> None: ...
-
-    def predict(self, inputs: Any, **model_kwargs: Any) -> Any: ...
+    ARMNN = "armnn"


 class HasProfiling(Protocol):
    profiling: dict[str, float]


-class DetectedFace(TypedDict):
-    box: BoundingBox
-    score: float
-    landmarks: npt.NDArray[np.float32] | None
-
-
-class RecognizedFace(TypedDict):
-    box: BoundingBox
+class Face(TypedDict):
+    boundingBox: BoundingBox
    embedding: npt.NDArray[np.float32]
+    imageWidth: int
+    imageHeight: int
+    score: float


 def has_profiling(obj: Any) -> TypeGuard[HasProfiling]:
@@ -17,14 +17,13 @@ from pytest import MonkeyPatch
 from pytest_mock import MockerFixture

 from app.main import load, preload_models
-from app.models.clip.textual import MClipTextualEncoder, OpenClipTextualEncoder
-from app.models.clip.visual import OpenClipVisualEncoder
-from app.models.facial_recognition.recognition import FaceRecognizer

 from .config import Settings, log, settings
 from .models.base import InferenceModel
 from .models.cache import ModelCache
-from .schemas import ModelFormat, ModelTask, ModelType
+from .models.clip import MCLIPEncoder, OpenCLIPEncoder
+from .models.facial_recognition import FaceRecognizer
+from .schemas import ModelRuntime, ModelType


 class TestBase:
@@ -36,13 +35,13 @@ class TestBase:

    @pytest.mark.providers(CPU_EP)
    def test_sets_cpu_provider(self, providers: list[str]) -> None:
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.providers == self.CPU_EP

    @pytest.mark.providers(CUDA_EP)
    def test_sets_cuda_provider_if_available(self, providers: list[str]) -> None:
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.providers == self.CUDA_EP

@@ -51,7 +50,7 @@ class TestBase:
        mocked = mocker.patch("app.models.base.ort.capi._pybind_state")
        mocked.get_available_openvino_device_ids.return_value = ["GPU.0", "CPU"]

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.providers == self.OV_EP

@@ -60,25 +59,25 @@ class TestBase:
        mocked = mocker.patch("app.models.base.ort.capi._pybind_state")
        mocked.get_available_openvino_device_ids.return_value = ["CPU"]

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.providers == self.CPU_EP

    @pytest.mark.providers(CUDA_EP_OUT_OF_ORDER)
    def test_sets_providers_in_correct_order(self, providers: list[str]) -> None:
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.providers == self.CUDA_EP

    @pytest.mark.providers(TRT_EP)
    def test_ignores_unsupported_providers(self, providers: list[str]) -> None:
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.providers == self.CUDA_EP

    def test_sets_provider_kwarg(self) -> None:
        providers = ["CUDAExecutionProvider"]
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", providers=providers)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=providers)

        assert encoder.providers == providers

@@ -86,17 +85,15 @@ class TestBase:
        mocked = mocker.patch("app.models.base.ort.capi._pybind_state")
        mocked.get_available_openvino_device_ids.return_value = ["GPU.0", "CPU"]

-        encoder = OpenClipTextualEncoder(
-            "ViT-B-32__openai", providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"]
-        )
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"])

        assert encoder.provider_options == [
-            {"device_type": "GPU_FP32", "cache_dir": (encoder.cache_dir / "openvino").as_posix()},
+            {"device_type": "GPU_FP32"},
            {"arena_extend_strategy": "kSameAsRequested"},
        ]

    def test_sets_provider_options_kwarg(self) -> None:
-        encoder = OpenClipTextualEncoder(
+        encoder = OpenCLIPEncoder(
            "ViT-B-32__openai",
            providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"],
            provider_options=[],
@@ -105,7 +102,7 @@ class TestBase:
        assert encoder.provider_options == []

    def test_sets_default_sess_options(self) -> None:
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.sess_options.execution_mode == ort.ExecutionMode.ORT_SEQUENTIAL
        assert encoder.sess_options.inter_op_num_threads == 1
@@ -113,9 +110,7 @@ class TestBase:
        assert encoder.sess_options.enable_cpu_mem_arena is False

    def test_sets_default_sess_options_does_not_set_threads_if_non_cpu_and_default_threads(self) -> None:
-        encoder = OpenClipTextualEncoder(
-            "ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"]
-        )
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"])

        assert encoder.sess_options.inter_op_num_threads == 0
        assert encoder.sess_options.intra_op_num_threads == 0
@@ -125,16 +120,14 @@ class TestBase:
        mock_settings.model_inter_op_threads = 2
        mock_settings.model_intra_op_threads = 4

-        encoder = OpenClipTextualEncoder(
-            "ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"]
-        )
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"])

        assert encoder.sess_options.inter_op_num_threads == 2
        assert encoder.sess_options.intra_op_num_threads == 4

    def test_sets_sess_options_kwarg(self) -> None:
        sess_options = ort.SessionOptions()
-        encoder = OpenClipTextualEncoder(
+        encoder = OpenCLIPEncoder(
            "ViT-B-32__openai",
            providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"],
            provider_options=[],
@@ -144,13 +137,13 @@ class TestBase:
        assert sess_options is encoder.sess_options

    def test_sets_default_cache_dir(self) -> None:
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

        assert encoder.cache_dir == Path(settings.cache_folder) / "clip" / "ViT-B-32__openai"

    def test_sets_cache_dir_kwarg(self) -> None:
        cache_dir = Path("/test_cache")
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=cache_dir)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=cache_dir)

        assert encoder.cache_dir == cache_dir

@@ -158,29 +151,29 @@ class TestBase:
        mocker.patch.object(settings, "ann", True)
        mocker.patch("ann.ann.is_available", False)

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

-        assert encoder.preferred_runtime == ModelFormat.ONNX
+        assert encoder.preferred_runtime == ModelRuntime.ONNX

    def test_sets_default_preferred_runtime_to_armnn_if_available(self, mocker: MockerFixture) -> None:
        mocker.patch.object(settings, "ann", True)
        mocker.patch("ann.ann.is_available", True)

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")

-        assert encoder.preferred_runtime == ModelFormat.ARMNN
+        assert encoder.preferred_runtime == ModelRuntime.ARMNN

    def test_sets_preferred_runtime_kwarg(self, mocker: MockerFixture) -> None:
        mocker.patch.object(settings, "ann", False)
        mocker.patch("ann.ann.is_available", False)

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", preferred_runtime=ModelFormat.ARMNN)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", preferred_runtime=ModelRuntime.ARMNN)

-        assert encoder.preferred_runtime == ModelFormat.ARMNN
+        assert encoder.preferred_runtime == ModelRuntime.ARMNN

    def test_casts_cache_dir_string_to_path(self) -> None:
        cache_dir = "/test_cache"
-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=cache_dir)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=cache_dir)

        assert encoder.cache_dir == Path(cache_dir)

@@ -193,7 +186,7 @@ class TestBase:
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
        info = mocker.spy(log, "info")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        encoder.clear_cache()

        mock_rmtree.assert_called_once_with(encoder.cache_dir)
@@ -208,7 +201,7 @@ class TestBase:
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
        warning = mocker.spy(log, "warning")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        encoder.clear_cache()

        mock_rmtree.assert_not_called()
@@ -222,7 +215,7 @@ class TestBase:
        mock_cache_dir.is_dir.return_value = True
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        with pytest.raises(RuntimeError):
            encoder.clear_cache()

@@ -237,7 +230,7 @@ class TestBase:
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
        warning = mocker.spy(log, "warning")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        encoder.clear_cache()

        mock_rmtree.assert_not_called()
@@ -252,7 +245,7 @@ class TestBase:
        mock_model_path.with_suffix.return_value = mock_model_path
        mock_ann = mocker.patch("app.models.base.AnnSession")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
        encoder._make_session(mock_model_path)

        mock_ann.assert_called_once()
@@ -269,8 +262,9 @@ class TestBase:

        mock_ann = mocker.patch("app.models.base.AnnSession")
        mock_ort = mocker.patch("app.models.base.ort.InferenceSession")
+        mocker.patch("app.models.base.os.chdir")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
        encoder._make_session(mock_armnn_path)

        mock_ort.assert_called_once()
@@ -284,17 +278,37 @@ class TestBase:
        mock_ann = mocker.patch("app.models.base.AnnSession")
        mock_ort = mocker.patch("app.models.base.ort.InferenceSession")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
        with pytest.raises(ValueError):
            encoder._make_session(mock_model_path)

        mock_ann.assert_not_called()
        mock_ort.assert_not_called()

+    def test_make_session_changes_cwd(self, mocker: MockerFixture) -> None:
+        mock_model_path = mocker.Mock()
+        mock_model_path.is_file.return_value = True
+        mock_model_path.suffix = ".onnx"
+        mock_model_path.parent = "model_parent"
+        mock_model_path.with_suffix.return_value = mock_model_path
+        mock_ort = mocker.patch("app.models.base.ort.InferenceSession")
+        mock_chdir = mocker.patch("app.models.base.os.chdir")
+
+        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder._make_session(mock_model_path)
+
+        mock_chdir.assert_has_calls(
+            [
+                mock.call(mock_model_path.parent),
+                mock.call(os.getcwd()),
+            ]
+        )
+        mock_ort.assert_called_once()
+
    def test_download(self, mocker: MockerFixture) -> None:
        mock_snapshot_download = mocker.patch("app.models.base.snapshot_download")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir="/path/to/cache")
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="/path/to/cache")
        encoder.download()

        mock_snapshot_download.assert_called_once_with(
@@ -308,7 +322,7 @@ class TestBase:
    def test_download_downloads_armnn_if_preferred_runtime(self, mocker: MockerFixture) -> None:
        mock_snapshot_download = mocker.patch("app.models.base.snapshot_download")

-        encoder = OpenClipTextualEncoder("ViT-B-32__openai", preferred_runtime=ModelFormat.ARMNN)
+        encoder = OpenCLIPEncoder("ViT-B-32__openai", preferred_runtime=ModelRuntime.ARMNN)
        encoder.download()

        mock_snapshot_download.assert_called_once_with(
@@ -330,18 +344,21 @@ class TestCLIP:
        mocker: MockerFixture,
        clip_model_cfg: dict[str, Any],
        clip_preprocess_cfg: Callable[[Path], dict[str, Any]],
+        clip_tokenizer_cfg: Callable[[Path], dict[str, Any]],
    ) -> None:
-        mocker.patch.object(OpenClipVisualEncoder, "download")
-        mocker.patch.object(OpenClipVisualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(OpenClipVisualEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "download")
+        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)

        mocked = mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
        mocked.run.return_value = [[self.embedding]]
        mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True)

-        clip_encoder = OpenClipVisualEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="vision")
+        clip_encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="vision")
        embedding = clip_encoder.predict(pil_image)

+        assert clip_encoder.mode == "vision"
        assert isinstance(embedding, np.ndarray)
        assert embedding.shape[0] == clip_model_cfg["embed_dim"]
        assert embedding.dtype == np.float32
@@ -351,19 +368,22 @@ class TestCLIP:
        self,
        mocker: MockerFixture,
        clip_model_cfg: dict[str, Any],
+        clip_preprocess_cfg: Callable[[Path], dict[str, Any]],
        clip_tokenizer_cfg: Callable[[Path], dict[str, Any]],
    ) -> None:
-        mocker.patch.object(OpenClipTextualEncoder, "download")
-        mocker.patch.object(OpenClipTextualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(OpenClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "download")
+        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)

        mocked = mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
        mocked.run.return_value = [[self.embedding]]
        mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True)

-        clip_encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
+        clip_encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
        embedding = clip_encoder.predict("test search query")

+        assert clip_encoder.mode == "text"
        assert isinstance(embedding, np.ndarray)
        assert embedding.shape[0] == clip_model_cfg["embed_dim"]
        assert embedding.dtype == np.float32
@@ -373,16 +393,18 @@ class TestCLIP:
        self,
        mocker: MockerFixture,
        clip_model_cfg: dict[str, Any],
+        clip_preprocess_cfg: Callable[[Path], dict[str, Any]],
        clip_tokenizer_cfg: Callable[[Path], dict[str, Any]],
    ) -> None:
-        mocker.patch.object(OpenClipTextualEncoder, "download")
-        mocker.patch.object(OpenClipTextualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(OpenClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "download")
+        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
        mock_tokenizer = mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True).return_value
        mock_ids = [randint(0, 50000) for _ in range(77)]
        mock_tokenizer.encode.return_value = SimpleNamespace(ids=mock_ids)

-        clip_encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
+        clip_encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
        clip_encoder._load_tokenizer()
        tokens = clip_encoder.tokenize("test search query")

@@ -396,17 +418,19 @@ class TestCLIP:
        self,
        mocker: MockerFixture,
        clip_model_cfg: dict[str, Any],
+        clip_preprocess_cfg: Callable[[Path], dict[str, Any]],
        clip_tokenizer_cfg: Callable[[Path], dict[str, Any]],
    ) -> None:
-        mocker.patch.object(MClipTextualEncoder, "download")
-        mocker.patch.object(MClipTextualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(MClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "download")
+        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
        mock_tokenizer = mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True).return_value
        mock_ids = [randint(0, 50000) for _ in range(77)]
        mock_attention_mask = [randint(0, 1) for _ in range(77)]
        mock_tokenizer.encode.return_value = SimpleNamespace(ids=mock_ids, attention_mask=mock_attention_mask)

-        clip_encoder = MClipTextualEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
+        clip_encoder = MCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
        clip_encoder._load_tokenizer()
        tokens = clip_encoder.tokenize("test search query")

@@ -437,12 +461,12 @@ class TestFaceRecognition:
        score = np.array([[0.67]] * num_faces).astype(np.float32)
        kpss = np.random.rand(num_faces, 5, 2).astype(np.float32)
        det_model.detect.return_value = (np.concatenate([bbox, score], axis=-1), kpss)
-        face_recognizer.model = det_model
+        face_recognizer.det_model = det_model

        rec_model = mock.Mock()
        embedding = np.random.rand(num_faces, 512).astype(np.float32)
        rec_model.get_feat.return_value = embedding
-        face_recognizer.model = rec_model
+        face_recognizer.rec_model = rec_model

        faces = face_recognizer.predict(cv_image)

@@ -462,28 +486,24 @@ class TestFaceRecognition:
 class TestCache:
    async def test_caches(self, mock_get_model: mock.Mock) -> None:
        model_cache = ModelCache()
-        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION)
-        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION)
+        await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION)
+        await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION)
        assert len(model_cache.cache._cache) == 1
        mock_get_model.assert_called_once()

    async def test_kwargs_used(self, mock_get_model: mock.Mock) -> None:
        model_cache = ModelCache()
-        await model_cache.get(
-            "test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, cache_dir="test_cache"
-        )
-        mock_get_model.assert_called_once_with(
-            ModelTask.FACIAL_RECOGNITION, ModelType.RECOGNITION, "test_model_name", cache_dir="test_cache"
-        )
+        await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION, cache_dir="test_cache")
+        mock_get_model.assert_called_once_with(ModelType.FACIAL_RECOGNITION, "test_model_name", cache_dir="test_cache")

    async def test_different_clip(self, mock_get_model: mock.Mock) -> None:
        model_cache = ModelCache()
-        await model_cache.get("test_image_model_name", ModelType.VISUAL, ModelTask.SEARCH)
-        await model_cache.get("test_text_model_name", ModelType.TEXTUAL, ModelTask.SEARCH)
+        await model_cache.get("test_image_model_name", ModelType.CLIP)
+        await model_cache.get("test_text_model_name", ModelType.CLIP)
        mock_get_model.assert_has_calls(
            [
-                mock.call(ModelTask.SEARCH, "test_image_model_name"),
-                mock.call(ModelTask.SEARCH, "test_text_model_name"),
+                mock.call(ModelType.CLIP, "test_image_model_name"),
+                mock.call(ModelType.CLIP, "test_text_model_name"),
            ]
        )
        assert len(model_cache.cache._cache) == 2
@@ -491,19 +511,19 @@ class TestCache:
    @mock.patch("app.models.cache.OptimisticLock", autospec=True)
    async def test_model_ttl(self, mock_lock_cls: mock.Mock, mock_get_model: mock.Mock) -> None:
        model_cache = ModelCache()
-        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, ttl=100)
+        await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION, ttl=100)
        mock_lock_cls.return_value.__aenter__.return_value.cas.assert_called_with(mock.ANY, ttl=100)

    @mock.patch("app.models.cache.SimpleMemoryCache.expire")
    async def test_revalidate_get(self, mock_cache_expire: mock.Mock, mock_get_model: mock.Mock) -> None:
        model_cache = ModelCache(revalidate=True)
-        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, ttl=100)
-        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, ttl=100)
+        await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION, ttl=100)
+        await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION, ttl=100)
        mock_cache_expire.assert_called_once_with(mock.ANY, 100)

    async def test_profiling(self, mock_get_model: mock.Mock) -> None:
        model_cache = ModelCache(profiling=True)
-        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, ttl=100)
+        await model_cache.get("test_model_name", ModelType.FACIAL_RECOGNITION, ttl=100)
        profiling = await model_cache.get_profiling()
        assert isinstance(profiling, dict)
        assert profiling == model_cache.cache.profiling
@@ -511,9 +531,9 @@ class TestCache:
    async def test_loads_mclip(self) -> None:
        model_cache = ModelCache()

-        model = await model_cache.get("XLM-Roberta-Large-Vit-B-32", ModelType.TEXTUAL, ModelTask.SEARCH)
+        model = await model_cache.get("XLM-Roberta-Large-Vit-B-32", ModelType.CLIP, mode="text")

-        assert isinstance(model, MClipTextualEncoder)
+        assert isinstance(model, MCLIPEncoder)
        assert model.model_name == "XLM-Roberta-Large-Vit-B-32"

    async def test_raises_exception_if_invalid_model_type(self) -> None:
@@ -521,13 +541,13 @@ class TestCache:
        model_cache = ModelCache()

        with pytest.raises(ValueError):
-            await model_cache.get("XLM-Roberta-Large-Vit-B-32", ModelType.TEXTUAL, invalid)
+            await model_cache.get("XLM-Roberta-Large-Vit-B-32", invalid, mode="text")

    async def test_raises_exception_if_unknown_model_name(self) -> None:
        model_cache = ModelCache()

        with pytest.raises(ValueError):
-            await model_cache.get("test_model_name", ModelType.TEXTUAL, ModelTask.SEARCH)
+            await model_cache.get("test_model_name", ModelType.CLIP, mode="text")

    async def test_preloads_models(self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock) -> None:
        os.environ["MACHINE_LEARNING_PRELOAD__CLIP"] = "ViT-B-32__openai"
@@ -542,12 +562,11 @@ class TestCache:
        monkeypatch.setattr("app.main.model_cache", model_cache)

        await preload_models(settings.preload)
-        assert len(model_cache.cache._cache) == 3
-        assert mock_get_model.call_count == 3
-        await model_cache.get("ViT-B-32__openai", ModelType.TEXTUAL, ModelTask.SEARCH, ttl=100)
-        await model_cache.get("ViT-B-32__openai", ModelType.VISUAL, ModelTask.SEARCH, ttl=100)
-        await model_cache.get("buffalo_s", ModelType.PIPELINE, ModelTask.FACIAL_RECOGNITION, ttl=100)
-        assert mock_get_model.call_count == 3
+        assert len(model_cache.cache._cache) == 2
+        assert mock_get_model.call_count == 2
+        await model_cache.get("ViT-B-32__openai", ModelType.CLIP, ttl=100)
+        await model_cache.get("buffalo_s", ModelType.FACIAL_RECOGNITION, ttl=100)
+        assert mock_get_model.call_count == 2


@pytest.mark.asyncio
@@ -574,8 +593,7 @@ class TestLoad:
    async def test_load_clears_cache_and_retries_if_os_error(self) -> None:
        mock_model = mock.Mock(spec=InferenceModel)
        mock_model.model_name = "test_model_name"
-        mock_model.model_type = ModelType.VISUAL
-        mock_model.model_task = ModelTask.SEARCH
+        mock_model.model_type = ModelType.CLIP
        mock_model.load.side_effect = [OSError, None]
        mock_model.loaded = False

@@ -1,4 +1,4 @@
-FROM mambaorg/micromamba:bookworm-slim@sha256:3624db3aee11d2f3f00d25f691aaaf8834b8bc4ec1b340dcdb48ef37281ea604 as builder
+FROM mambaorg/micromamba:bookworm-slim@sha256:96586e238e2fed914b839e50cf91943b5655262348d141466b34ced2e0b5b155 as builder

 ENV NODE_ENV=production \
  TRANSFORMERS_CACHE=/cache \
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.1 and should not be changed by hand.

 [[package]]
 name = "aiocache"
@@ -877,13 +877,13 @@ tqdm = ["tqdm"]

 [[package]]
 name = "ftfy"
-version = "6.2.0"
+version = "6.1.3"
 description = "Fixes mojibake and other problems with Unicode, after the fact"
 optional = false
 python-versions = ">=3.8,<4"
 files = [
-    {file = "ftfy-6.2.0-py3-none-any.whl", hash = "sha256:f94a2c34b76e07475720e3096f5ca80911d152406fbde66fdb45c4d0c9150026"},
-    {file = "ftfy-6.2.0.tar.gz", hash = "sha256:5e42143c7025ef97944ca2619d6b61b0619fc6654f98771d39e862c1424c75c0"},
+    {file = "ftfy-6.1.3-py3-none-any.whl", hash = "sha256:e49c306c06a97f4986faa7a8740cfe3c13f3106e85bcec73eb629817e671557c"},
+    {file = "ftfy-6.1.3.tar.gz", hash = "sha256:693274aead811cff24c1e8784165aa755cd2f6e442a5ec535c7d697f6422a422"},
 ]

 [package.dependencies]
@@ -1274,13 +1274,13 @@ socks = ["socksio (==1.*)"]

 [[package]]
 name = "huggingface-hub"
-version = "0.22.2"
+version = "0.21.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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-    {file = "huggingface_hub-0.22.2.tar.gz", hash = "sha256:32e9a9a6843c92f253ff9ca16b9985def4d80a93fb357af5353f770ef74a81be"},
+    {file = "huggingface_hub-0.21.4-py3-none-any.whl", hash = "sha256:df37c2c37fc6c82163cdd8a67ede261687d80d1e262526d6c0ce73b6b3630a7b"},
+    {file = "huggingface_hub-0.21.4.tar.gz", hash = "sha256:e1f4968c93726565a80edf6dc309763c7b546d0cfe79aa221206034d50155531"},
 ]

 [package.dependencies]
@@ -1293,16 +1293,15 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"

 [package.extras]
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+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 cli = ["InquirerPy (==0.3.4)"]
-dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
 hf-transfer = ["hf-transfer (>=0.1.4)"]
-inference = ["aiohttp", "minijinja (>=1.0)"]
-quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
+inference = ["aiohttp", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)"]
+quality = ["mypy (==1.5.1)", "ruff (>=0.1.3)"]
 tensorflow = ["graphviz", "pydot", "tensorflow"]
-tensorflow-testing = ["keras (<3.0)", "tensorflow"]
-testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
 torch = ["safetensors", "torch"]
 typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]

@@ -1568,13 +1567,13 @@ test = ["pytest (>=7.4)", "pytest-cov (>=4.1)"]

 [[package]]
 name = "locust"
-version = "2.24.1"
+version = "2.24.0"
 description = "Developer friendly load testing framework"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "locust-2.24.0.tar.gz", hash = "sha256:6cffa378d995244a7472af6be1d6139331f19aee44e907deee73e0281252804d"},
 ]

 [package.dependencies]
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+version = "1.8.0"
 description = "Optional static typing for Python"
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 python-versions = ">=3.8"
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 [package.dependencies]
@@ -2065,22 +2064,21 @@ reference = "cuda12"

 [[package]]
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 description = "ONNX Runtime is a runtime accelerator for Machine Learning models"
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 python-versions = "*"
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 ]

 [package.dependencies]
 coloredlogs = "*"
 flatbuffers = "*"
-numpy = ">=1.25.2"
+numpy = ">=1.21.6"
 packaging = "*"
 protobuf = "*"
 sympy = "*"
@@ -2291,13 +2289,13 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-co

 [[package]]
 name = "pluggy"
-version = "1.4.0"
+version = "1.3.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]

 [package.extras]
@@ -2474,13 +2472,13 @@ files = [

 [[package]]
 name = "pytest"
-version = "8.1.1"
+version = "8.0.2"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]

 [package.dependencies]
@@ -2488,21 +2486,21 @@ colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
 iniconfig = "*"
 packaging = "*"
-pluggy = ">=1.4,<2.0"
-tomli = {version = ">=1", markers = "python_version < \"3.11\""}
+pluggy = ">=1.3.0,<2.0"
+tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}

 [package.extras]
-testing = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]

 [[package]]
 name = "pytest-asyncio"
-version = "0.23.6"
+version = "0.23.5"
 description = "Pytest support for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pytest-asyncio-0.23.6.tar.gz", hash = "sha256:ffe523a89c1c222598c76856e76852b787504ddb72dd5d9b6617ffa8aa2cde5f"},
-    {file = "pytest_asyncio-0.23.6-py3-none-any.whl", hash = "sha256:68516fdd1018ac57b846c9846b954f0393b26f094764a28c955eabb0536a4e8a"},
+    {file = "pytest-asyncio-0.23.5.tar.gz", hash = "sha256:3a048872a9c4ba14c3e90cc1aa20cbc2def7d01c7c8db3777ec281ba9c057675"},
+    {file = "pytest_asyncio-0.23.5-py3-none-any.whl", hash = "sha256:4e7093259ba018d58ede7d5315131d21923a60f8a6e9ee266ce1589685c89eac"},
 ]

 [package.dependencies]
@@ -2532,17 +2530,17 @@ testing = ["fields", "hunter", "process-tests", "pytest-xdist", "six", "virtuale

 [[package]]
 name = "pytest-mock"
-version = "3.14.0"
+version = "3.12.0"
 description = "Thin-wrapper around the mock package for easier use with pytest"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "pytest-mock-3.12.0.tar.gz", hash = "sha256:31a40f038c22cad32287bb43932054451ff5583ff094bca6f675df2f8bc1a6e9"},
+    {file = "pytest_mock-3.12.0-py3-none-any.whl", hash = "sha256:0972719a7263072da3a21c7f4773069bcc7486027d7e8e1f81d98a47e701bc4f"},
 ]

 [package.dependencies]
-pytest = ">=6.2.5"
+pytest = ">=5.0"

 [package.extras]
 dev = ["pre-commit", "pytest-asyncio", "tox"]
@@ -2845,28 +2843,28 @@ files = [

 [[package]]
 name = "ruff"
-version = "0.3.4"
+version = "0.3.2"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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 [[package]]
@@ -3290,13 +3288,13 @@ zstd = ["zstandard (>=0.18.0)"]

 [[package]]
 name = "uvicorn"
-version = "0.29.0"
+version = "0.27.1"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "uvicorn-0.27.1.tar.gz", hash = "sha256:3d9a267296243532db80c83a959a3400502165ade2c1338dea4e67915fd4745a"},
 ]

 [package.dependencies]
@@ -3628,4 +3626,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.12"
-content-hash = "1b014276ec94f9389459a70d31f0d96d1dd5a138bcc988900865e5f07a72bc62"
+content-hash = "c947090d326e81179054b7ce4dded311df8b7ca5a56680d5e9459cf8ca18df1a"
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "machine-learning"
-version = "1.100.0"
+version = "1.98.2"
 description = ""
 authors = ["Hau Tran <alex.tran1502@gmail.com>"]
 readme = "README.md"
@@ -51,7 +51,7 @@ onnxruntime-gpu = {version = "^1.17.0", source = "cuda12"}
 optional = true

 [tool.poetry.group.openvino.dependencies]
-onnxruntime-openvino = "^1.17.1"
+onnxruntime-openvino = ">=1.15.0,<1.16.0"

 [tool.poetry.group.armnn]
 optional = true
--- a/Show More
+++ b/Show More