chore(mobile): better second to first assets shown

chore(mobile): post release task (#10228 )
Version v1.106.3
2024-06-12 16:58:58 -05:00 · 2024-06-12 14:17:58 -05:00 · 2024-06-12 18:26:10 +00:00 · 2024-06-12 12:43:01 -05:00 · 2024-06-12 12:51:46 -04:00 · 2024-06-12 17:37:46 +01:00
505 changed files with 35213 additions and 4825 deletions
@@ -4,6 +4,7 @@
 design/
 docker/
 !docker/scripts
 docs/
 e2e/
 fastlane/
@@ -0,0 +1,23 @@
 cli:
 - changed-files:
  - any-glob-to-any-file: cli/**
 documentation:
 - changed-files:
  - any-glob-to-any-file: docs/**
 🖥️web:
 - changed-files:
  - any-glob-to-any-file: web/**
 📱mobile:
 - changed-files:
  - any-glob-to-any-file: mobile/**
 🗄️server:
 - changed-files:
  - any-glob-to-any-file: server/**
 🧠machine-learning:
 - changed-files:
  - any-glob-to-any-file: machine-learning/**
@@ -1,16 +1,17 @@
 name: CLI Build
 on:
  workflow_dispatch:
  push:
    branches: [main]
    paths:
-      - "cli/**"
+      - 'cli/**'
-      - ".github/workflows/cli.yml"
+      - '.github/workflows/cli.yml'
  pull_request:
    branches: [main]
    paths:
-      - "cli/**"
+      - 'cli/**'
-      - ".github/workflows/cli.yml"
+      - '.github/workflows/cli.yml'
  release:
    types: [published]
 concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
@@ -32,8 +33,8 @@ jobs:
      # Setup .npmrc file to publish to npm
      - uses: actions/setup-node@v4
        with:
-          node-version: "20.x"
+          node-version: '20.x'
-          registry-url: "https://registry.npmjs.org"
+          registry-url: 'https://registry.npmjs.org'
      - name: Prepare SDK
        run: npm ci --prefix ../open-api/typescript-sdk/
      - name: Build SDK
@@ -41,7 +42,7 @@ jobs:
      - run: npm ci
      - run: npm run build
      - run: npm publish
-        if: ${{ github.event_name == 'workflow_dispatch' }}
+        if: ${{ github.event_name == 'release' }}
        env:
          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
@@ -83,15 +84,15 @@ jobs:
          images: |
            name=ghcr.io/${{ github.repository_owner }}/immich-cli
          tags: |
-            type=raw,value=${{ steps.package-version.outputs.version }},enable=${{ github.event_name == 'workflow_dispatch' }}
+            type=raw,value=${{ steps.package-version.outputs.version }},enable=${{ github.event_name == 'release' }}
-            type=raw,value=latest,enable=${{ github.event_name == 'workflow_dispatch' }}
+            type=raw,value=latest,enable=${{ github.event_name == 'release' }}
      - name: Build and push image
-        uses: docker/build-push-action@v5.3.0
+        uses: docker/build-push-action@v5.4.0
        with:
          file: cli/Dockerfile
          platforms: linux/amd64,linux/arm64
-          push: ${{ github.event_name == 'workflow_dispatch' }}
+          push: ${{ github.event_name == 'release' }}
          cache-from: type=gha
          cache-to: type=gha,mode=max
          tags: ${{ steps.metadata.outputs.tags }}
@@ -35,7 +35,7 @@ jobs:
    steps:
      - name: Clean temporary images
        if: "${{ env.TOKEN != '' }}"
-        uses: stumpylog/image-cleaner-action/ephemeral@v0.6.0
+        uses: stumpylog/image-cleaner-action/ephemeral@v0.7.0
        with:
          token: "${{ env.TOKEN }}"
          owner: "immich-app"
@@ -64,7 +64,7 @@ jobs:
    steps:
      - name: Clean untagged images
        if: "${{ env.TOKEN != '' }}"
-        uses: stumpylog/image-cleaner-action/untagged@v0.6.0
+        uses: stumpylog/image-cleaner-action/untagged@v0.7.0
        with:
          token: "${{ env.TOKEN }}"
          owner: "immich-app"
@@ -115,7 +115,7 @@ jobs:
          fi
      - name: Build and push image
-        uses: docker/build-push-action@v5.3.0
+        uses: docker/build-push-action@v5.4.0
        with:
          context: ${{ matrix.context }}
          file: ${{ matrix.file }}
@@ -0,0 +1,12 @@
 name: "Pull Request Labeler"
 on:
 - pull_request_target
 jobs:
  labeler:
    permissions:
      contents: read
      pull-requests: write
    runs-on: ubuntu-latest
    steps:
    - uses: actions/labeler@v5
@@ -1,13 +0,0 @@
 name: Enforce PR labels
 on:
  pull_request:
    types: [labeled, unlabeled, opened, edited, synchronize]
 jobs:
  enforce-label:
    name: Enforce label
    runs-on: ubuntu-latest
    steps:
    - if: toJson(github.event.pull_request.labels) == '[]'
      run: exit 1
@@ -10,12 +10,6 @@ dev-update:
 dev-scale:
 	docker compose -f ./docker/docker-compose.dev.yml up --build -V  --scale immich-server=3 --remove-orphans
 stage:
 	docker compose -f ./docker/docker-compose.staging.yml up --build -V --remove-orphans
 pull-stage:
 	docker compose -f ./docker/docker-compose.staging.yml pull
 .PHONY: e2e
 e2e:
 	docker compose -f ./e2e/docker-compose.yml up --build -V --remove-orphans
@@ -31,6 +31,7 @@
  <a href="readme_i18n/README_zh_CN.md">中文</a>
  <a href="readme_i18n/README_ru_RU.md">Русский</a>
  <a href="readme_i18n/README_pt_BR.md">Português Brasileiro</a>
  <a href="readme_i18n/README_sv_SE.md">Svenska</a>
  <a href="readme_i18n/README_ar_JO.md">العربية</a>
 </p>
@@ -1 +1 @@
-20.13
+20.14
@@ -1,4 +1,4 @@
-FROM node:20-alpine3.19@sha256:291e84d956f1aff38454bbd3da38941461ad569a185c20aa289f71f37ea08e23 as core
+FROM node:20-alpine3.19@sha256:696ae41fb5880949a15ade7879a2deae93b3f0723f757bdb5b8a9e4a744ce27f 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": "2.2.3",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@immich/cli",
-      "version": "2.2.0",
+      "version": "2.2.3",
      "license": "GNU Affero General Public License version 3",
      "dependencies": {
        "fast-glob": "^3.3.2",
@@ -47,7 +47,7 @@
    },
    "../open-api/typescript-sdk": {
      "name": "@immich/sdk",
-      "version": "1.105.1",
+      "version": "1.106.3",
      "dev": true,
      "license": "GNU Affero General Public License version 3",
      "dependencies": {
@@ -1138,9 +1138,9 @@
      }
    },
    "node_modules/@types/node": {
-      "version": "20.12.12",
+      "version": "20.12.13",
-      "resolved": "https://registry.npmjs.org/@types/node/-/node-20.12.12.tgz",
+      "resolved": "https://registry.npmjs.org/@types/node/-/node-20.12.13.tgz",
-      "integrity": "sha512-eWLDGF/FOSPtAvEqeRAQ4C8LSA7M1I7i0ky1I8U7kD1J5ITyW3AsRhQrKVoWf5pFKZ2kILsEGJhsI9r93PYnOw==",
+      "integrity": "sha512-gBGeanV41c1L171rR7wjbMiEpEI/l5XFQdLLfhr/REwpgDy/4U8y89+i8kRiLzDyZdOkXh+cRaTetUnCYutoXA==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
@@ -1154,17 +1154,17 @@
      "dev": true
    },
    "node_modules/@typescript-eslint/eslint-plugin": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/eslint-plugin/-/eslint-plugin-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/eslint-plugin/-/eslint-plugin-7.11.0.tgz",
-      "integrity": "sha512-PzCr+a/KAef5ZawX7nbyNwBDtM1HdLIT53aSA2DDlxmxMngZ43O8SIePOeX8H5S+FHXeI6t97mTt/dDdzY4Fyw==",
+      "integrity": "sha512-P+qEahbgeHW4JQ/87FuItjBj8O3MYv5gELDzr8QaQ7fsll1gSMTYb6j87MYyxwf3DtD7uGFB9ShwgmCJB5KmaQ==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
        "@eslint-community/regexpp": "^4.10.0",
-        "@typescript-eslint/scope-manager": "7.10.0",
+        "@typescript-eslint/scope-manager": "7.11.0",
-        "@typescript-eslint/type-utils": "7.10.0",
+        "@typescript-eslint/type-utils": "7.11.0",
-        "@typescript-eslint/utils": "7.10.0",
+        "@typescript-eslint/utils": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0",
+        "@typescript-eslint/visitor-keys": "7.11.0",
        "graphemer": "^1.4.0",
        "ignore": "^5.3.1",
        "natural-compare": "^1.4.0",
@@ -1188,16 +1188,16 @@
      }
    },
    "node_modules/@typescript-eslint/parser": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/parser/-/parser-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/parser/-/parser-7.11.0.tgz",
-      "integrity": "sha512-2EjZMA0LUW5V5tGQiaa2Gys+nKdfrn2xiTIBLR4fxmPmVSvgPcKNW+AE/ln9k0A4zDUti0J/GZXMDupQoI+e1w==",
+      "integrity": "sha512-yimw99teuaXVWsBcPO1Ais02kwJ1jmNA1KxE7ng0aT7ndr1pT1wqj0OJnsYVGKKlc4QJai86l/025L6z8CljOg==",
      "dev": true,
      "license": "BSD-2-Clause",
      "dependencies": {
-        "@typescript-eslint/scope-manager": "7.10.0",
+        "@typescript-eslint/scope-manager": "7.11.0",
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/typescript-estree": "7.10.0",
+        "@typescript-eslint/typescript-estree": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0",
+        "@typescript-eslint/visitor-keys": "7.11.0",
        "debug": "^4.3.4"
      },
      "engines": {
@@ -1217,14 +1217,14 @@
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    },
    "node_modules/@typescript-eslint/scope-manager": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/scope-manager/-/scope-manager-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/scope-manager/-/scope-manager-7.11.0.tgz",
-      "integrity": "sha512-7L01/K8W/VGl7noe2mgH0K7BE29Sq6KAbVmxurj8GGaPDZXPr8EEQ2seOeAS+mEV9DnzxBQB6ax6qQQ5C6P4xg==",
+      "integrity": "sha512-27tGdVEiutD4POirLZX4YzT180vevUURJl4wJGmm6TrQoiYwuxTIY98PBp6L2oN+JQxzE0URvYlzJaBHIekXAw==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0"
+        "@typescript-eslint/visitor-keys": "7.11.0"
      },
      "engines": {
        "node": "^18.18.0 || >=20.0.0"
@@ -1235,14 +1235,14 @@
      }
    },
    "node_modules/@typescript-eslint/type-utils": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/type-utils/-/type-utils-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/type-utils/-/type-utils-7.11.0.tgz",
-      "integrity": "sha512-D7tS4WDkJWrVkuzgm90qYw9RdgBcrWmbbRkrLA4d7Pg3w0ttVGDsvYGV19SH8gPR5L7OtcN5J1hTtyenO9xE9g==",
+      "integrity": "sha512-WmppUEgYy+y1NTseNMJ6mCFxt03/7jTOy08bcg7bxJJdsM4nuhnchyBbE8vryveaJUf62noH7LodPSo5Z0WUCg==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
-        "@typescript-eslint/typescript-estree": "7.10.0",
+        "@typescript-eslint/typescript-estree": "7.11.0",
-        "@typescript-eslint/utils": "7.10.0",
+        "@typescript-eslint/utils": "7.11.0",
        "debug": "^4.3.4",
        "ts-api-utils": "^1.3.0"
      },
@@ -1263,9 +1263,9 @@
      }
    },
    "node_modules/@typescript-eslint/types": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/types/-/types-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/types/-/types-7.11.0.tgz",
-      "integrity": "sha512-7fNj+Ya35aNyhuqrA1E/VayQX9Elwr8NKZ4WueClR3KwJ7Xx9jcCdOrLW04h51de/+gNbyFMs+IDxh5xIwfbNg==",
+      "integrity": "sha512-MPEsDRZTyCiXkD4vd3zywDCifi7tatc4K37KqTprCvaXptP7Xlpdw0NR2hRJTetG5TxbWDB79Ys4kLmHliEo/w==",
      "dev": true,
      "license": "MIT",
      "engines": {
@@ -1277,14 +1277,14 @@
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    },
    "node_modules/@typescript-eslint/typescript-estree": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/typescript-estree/-/typescript-estree-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/typescript-estree/-/typescript-estree-7.11.0.tgz",
-      "integrity": "sha512-LXFnQJjL9XIcxeVfqmNj60YhatpRLt6UhdlFwAkjNc6jSUlK8zQOl1oktAP8PlWFzPQC1jny/8Bai3/HPuvN5g==",
+      "integrity": "sha512-cxkhZ2C/iyi3/6U9EPc5y+a6csqHItndvN/CzbNXTNrsC3/ASoYQZEt9uMaEp+xFNjasqQyszp5TumAVKKvJeQ==",
      "dev": true,
      "license": "BSD-2-Clause",
      "dependencies": {
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0",
+        "@typescript-eslint/visitor-keys": "7.11.0",
        "debug": "^4.3.4",
        "globby": "^11.1.0",
        "is-glob": "^4.0.3",
@@ -1306,16 +1306,16 @@
      }
    },
    "node_modules/@typescript-eslint/utils": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/utils/-/utils-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/utils/-/utils-7.11.0.tgz",
-      "integrity": "sha512-olzif1Fuo8R8m/qKkzJqT7qwy16CzPRWBvERS0uvyc+DHd8AKbO4Jb7kpAvVzMmZm8TrHnI7hvjN4I05zow+tg==",
+      "integrity": "sha512-xlAWwPleNRHwF37AhrZurOxA1wyXowW4PqVXZVUNCLjB48CqdPJoJWkrpH2nij9Q3Lb7rtWindtoXwxjxlKKCA==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
        "@eslint-community/eslint-utils": "^4.4.0",
-        "@typescript-eslint/scope-manager": "7.10.0",
+        "@typescript-eslint/scope-manager": "7.11.0",
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/typescript-estree": "7.10.0"
+        "@typescript-eslint/typescript-estree": "7.11.0"
      },
      "engines": {
        "node": "^18.18.0 || >=20.0.0"
@@ -1329,13 +1329,13 @@
      }
    },
    "node_modules/@typescript-eslint/visitor-keys": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/visitor-keys/-/visitor-keys-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/visitor-keys/-/visitor-keys-7.11.0.tgz",
-      "integrity": "sha512-9ntIVgsi6gg6FIq9xjEO4VQJvwOqA3jaBFQJ/6TK5AvEup2+cECI6Fh7QiBxmfMHXU0V0J4RyPeOU1VDNzl9cg==",
+      "integrity": "sha512-7syYk4MzjxTEk0g/w3iqtgxnFQspDJfn6QKD36xMuuhTzjcxY7F8EmBLnALjVyaOF1/bVocu3bS/2/F7rXrveQ==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
        "eslint-visitor-keys": "^3.4.3"
      },
      "engines": {
@@ -4281,10 +4281,11 @@
      }
    },
    "node_modules/vite": {
-      "version": "5.2.11",
+      "version": "5.2.12",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-5.2.11.tgz",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-5.2.12.tgz",
-      "integrity": "sha512-HndV31LWW05i1BLPMUCE1B9E9GFbOu1MbenhS58FuK6owSO5qHm7GiCotrNY1YE5rMeQSFBGmT5ZaLEjFizgiQ==",
+      "integrity": "sha512-/gC8GxzxMK5ntBwb48pR32GGhENnjtY30G4A0jemunsBkiEZFw60s8InGpN8gkhHEkjnRK1aSAxeQgwvFhUHAA==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
        "esbuild": "^0.20.1",
        "postcss": "^8.4.38",
@@ -1,6 +1,6 @@
 {
  "name": "@immich/cli",
-  "version": "2.2.0",
+  "version": "2.2.3",
  "description": "Command Line Interface (CLI) for Immich",
  "type": "module",
  "exports": "./dist/index.js",
@@ -62,6 +62,6 @@
    "lodash-es": "^4.17.21"
  },
  "volta": {
-    "node": "20.13.1"
+    "node": "20.14.0"
  }
 }
@@ -2,24 +2,37 @@
 # Manual edits may be lost in future updates.
 provider "registry.opentofu.org/cloudflare/cloudflare" {
-  version     = "4.33.0"
+  version     = "4.34.0"
-  constraints = "4.33.0"
+  constraints = "4.34.0"
  hashes = [
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+    "h1:2+1lKObDDdFZRluvROF3RKtXD66CFT3PfnHOvR6CmfA=",
-    "zh:1fd94992cbb8ce2943cf4fe3deff01b9b1a0e913d2cdd484ceb96a859d46dc5d",
+    "h1:7vluN2wmw8D9nI11YwTgoGv3hGDXlkt8xqQ4L/JABeQ=",
-    "zh:2b4f37c16a7f6d3712b03980b52b149d4ef6a544917bfe1d1c2ca2d40468daa5",
+    "h1:B0Urm8ZKTJ8cXzSCtEpJ+o+LsD8MXaD6LU59qVbh50Q=",
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+    "h1:FpGLCm5oF12FaRti3E4iQJlkVbdCC7toyGVuH8og7KY=",
-    "zh:6468dee137fa07b0b43f742cfdaabb6620883b00773af370e10755ba579eb7f7",
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    "zh:1e1a545e83e6457a0e15357b23139bc288fb4fbd5e9a5ddfedc95a6a0216b08c",
    "zh:29eef2621e0b1501f620e615bf73b1b90d5417d745e38af63634bc03250faf87",
    "zh:3c20989d7e1e141882e6091384bf85fdc83f70f3d29e3e047c493a07de992095",
    "zh:3d39619379ba29c7ffb15196f0ea72a04c84cfcdf4b39ac42ac4cf4c19f3eae2",
    "zh:805f4a2774e9279c590b8214aabe6df9dcc22bb995df2530513f2f78c647ce75",
    "zh:890df766e9b839623b1f0437355032a3c006226a6c200cd911e15ee1a9014e9f",
-    "zh:94420269672dc5bef37e1a8efab656ada5c2d6f162b52cc59ea74cf0cf35d633",
+    "zh:8af716f8655a57aa986861a8a7fa1d724594a284bd77c870eaea4db5f8b9732d",
-    "zh:972481b86636f00771c2b5f3e408ffd9b66d42942645c8b8e11c4f4bf52285f1",
+    "zh:a3d13c93b4e6ee6004782debaa9a17f990f2fe8ec8ba545c232818bb6064aba9",
-    "zh:ac52d6698fa8b2a8ab820ffb59381da27684a205f5a78529b56358efab67fe06",
+    "zh:bfa136acf82d3719473c0064446cc16d1b0303d98b06f55f503b7abeebceadb1",
-    "zh:c924c7ac3a8fc08eff7588627be68fc94958c1aaa65928a9fd73cf1d610a0dbf",
+    "zh:ca6cf9254ae5436f2efbc01a0e3f7e4aa3c08b45182037b3eb3eb9539b2f7aec",
-    "zh:cfdfaeab3fcb522a806fc5b71cbd6096df0fafa06cea2131c0db6074b3b76eed",
+    "zh:cba32d5de02674004e0a5955bd5222016d9991ca0553d4bd3bea517cd9def6ab",
-    "zh:d554393736b99bd1f0b60e210e276531bcd8df79f435924879eeecc1a2100a0d",
+    "zh:d22c8cd527c6d0e84567f57be5911792e2fcd5969e3bba3747489f18bb16705b",
-    "zh:df827b0e00c9e2d666cfe6409f61446908e5983a07ae32c822ef193f6b56c37c",
+    "zh:e4eeede9b3e72cdadd6cc252d4cbcf41baee6ecfd12bacd927e2dcbe733ab210",
    "zh:facdaa787a69f86203cd3cc6922baea0b4a18bd9c36b0a8162e2e88ef6c90655",
  ]
 }
@@ -5,7 +5,7 @@ terraform {
  required_providers {
    cloudflare = {
      source = "cloudflare/cloudflare"
-      version = "4.33.0"
+      version = "4.34.0"
    }
  }
 }
@@ -2,24 +2,37 @@
 # Manual edits may be lost in future updates.
 provider "registry.opentofu.org/cloudflare/cloudflare" {
-  version     = "4.33.0"
+  version     = "4.34.0"
-  constraints = "4.33.0"
+  constraints = "4.34.0"
  hashes = [
-    "h1:jfvnxO1kjxUquizrBlswsytWQeHXjvNz6IZwPTuixJ4=",
+    "h1:+W0+Xe1AUh7yvHjDbgR9T7CY1UbBC3Y6U7Eo+ucLnJM=",
-    "zh:1839d03c8c30d3eac4f18c78c5c095d44348eb06cc9d758136d16517094b64e3",
+    "h1:2+1lKObDDdFZRluvROF3RKtXD66CFT3PfnHOvR6CmfA=",
-    "zh:1fd94992cbb8ce2943cf4fe3deff01b9b1a0e913d2cdd484ceb96a859d46dc5d",
+    "h1:7vluN2wmw8D9nI11YwTgoGv3hGDXlkt8xqQ4L/JABeQ=",
-    "zh:2b4f37c16a7f6d3712b03980b52b149d4ef6a544917bfe1d1c2ca2d40468daa5",
+    "h1:B0Urm8ZKTJ8cXzSCtEpJ+o+LsD8MXaD6LU59qVbh50Q=",
-    "zh:32ecb8017be0a34f72b9b0fcd43d944b99cdc903c79892a68b48719824fb194c",
+    "h1:FpGLCm5oF12FaRti3E4iQJlkVbdCC7toyGVuH8og7KY=",
-    "zh:6468dee137fa07b0b43f742cfdaabb6620883b00773af370e10755ba579eb7f7",
+    "h1:FunTmrCMDy+rom7YskY0WiL5/Y164zFrrD9xnBxU5NY=",
-    "zh:766504de95a418fd763d9474f39fb147053201d6c4efa3efa456fb39a559b28b",
+    "h1:GrxZhEb+5HzmHF/BvZBdGKBJy6Wyjme0+ABVDz/63to=",
-    "zh:800342078c0c04a36cb2558d0c5c6bf050a8b4c231abecac59e56c9868b9fa7e",
+    "h1:J36dda2K42/oTfHuZ4jKkW5+nI6BTWFRUvo60P17NJg=",
    "h1:Kq0Wyn+j6zoQeghMYixbnfnyP9ZSIEJbOCzMbaCiAQQ=",
    "h1:TKxunXCiS/z105sN/kBNFwU6tIKD67JKJ3ZKjwzoCuI=",
    "h1:TR0URKFQxsRO5/v7bKm5hkD/CTTjsG7aVGllL/Mf25c=",
    "h1:V+3Qs0Reb6r+8p4XjE5ZFDWYrOIN0x5SwORz4wvHOJ4=",
    "h1:mZB3Ui7V/lPQMQK53eBOjIHcrul74252dT06Kgn3J+s=",
    "h1:wJwZrIXxoki8omXLJ7XA7B1KaSrtcLMJp090fRtFRAc=",
    "zh:02aa46743c1585ada8faa7db23af68ea614053a506f88f05d1090ff5e0e68076",
    "zh:1e1a545e83e6457a0e15357b23139bc288fb4fbd5e9a5ddfedc95a6a0216b08c",
    "zh:29eef2621e0b1501f620e615bf73b1b90d5417d745e38af63634bc03250faf87",
    "zh:3c20989d7e1e141882e6091384bf85fdc83f70f3d29e3e047c493a07de992095",
    "zh:3d39619379ba29c7ffb15196f0ea72a04c84cfcdf4b39ac42ac4cf4c19f3eae2",
    "zh:805f4a2774e9279c590b8214aabe6df9dcc22bb995df2530513f2f78c647ce75",
    "zh:890df766e9b839623b1f0437355032a3c006226a6c200cd911e15ee1a9014e9f",
-    "zh:94420269672dc5bef37e1a8efab656ada5c2d6f162b52cc59ea74cf0cf35d633",
+    "zh:8af716f8655a57aa986861a8a7fa1d724594a284bd77c870eaea4db5f8b9732d",
-    "zh:972481b86636f00771c2b5f3e408ffd9b66d42942645c8b8e11c4f4bf52285f1",
+    "zh:a3d13c93b4e6ee6004782debaa9a17f990f2fe8ec8ba545c232818bb6064aba9",
-    "zh:ac52d6698fa8b2a8ab820ffb59381da27684a205f5a78529b56358efab67fe06",
+    "zh:bfa136acf82d3719473c0064446cc16d1b0303d98b06f55f503b7abeebceadb1",
-    "zh:c924c7ac3a8fc08eff7588627be68fc94958c1aaa65928a9fd73cf1d610a0dbf",
+    "zh:ca6cf9254ae5436f2efbc01a0e3f7e4aa3c08b45182037b3eb3eb9539b2f7aec",
-    "zh:cfdfaeab3fcb522a806fc5b71cbd6096df0fafa06cea2131c0db6074b3b76eed",
+    "zh:cba32d5de02674004e0a5955bd5222016d9991ca0553d4bd3bea517cd9def6ab",
-    "zh:d554393736b99bd1f0b60e210e276531bcd8df79f435924879eeecc1a2100a0d",
+    "zh:d22c8cd527c6d0e84567f57be5911792e2fcd5969e3bba3747489f18bb16705b",
-    "zh:df827b0e00c9e2d666cfe6409f61446908e5983a07ae32c822ef193f6b56c37c",
+    "zh:e4eeede9b3e72cdadd6cc252d4cbcf41baee6ecfd12bacd927e2dcbe733ab210",
    "zh:facdaa787a69f86203cd3cc6922baea0b4a18bd9c36b0a8162e2e88ef6c90655",
  ]
 }
@@ -5,7 +5,7 @@ terraform {
  required_providers {
    cloudflare = {
      source = "cloudflare/cloudflare"
-      version = "4.33.0"
+      version = "4.34.0"
    }
  }
 }
@@ -84,7 +84,7 @@ services:
  redis:
    container_name: immich_redis
-    image: redis:6.2-alpine@sha256:e31ca60b18f7e9b78b573d156702471d4eda038803c0b8e6f01559f350031e93
+    image: redis:6.2-alpine@sha256:d6c2911ac51b289db208767581a5d154544f2b2fe4914ea5056443f62dc6e900
    healthcheck:
      test: redis-cli ping || exit 1
@@ -103,7 +103,7 @@ services:
    ports:
      - 5432:5432
    healthcheck:
-      test: pg_isready --dbname='${DB_DATABASE_NAME}' || exit 1; Chksum="$$(psql --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' --tuples-only --no-align --command='SELECT SUM(checksum_failures) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
+      test: pg_isready --dbname='${DB_DATABASE_NAME}' || exit 1; Chksum="$$(psql --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' --tuples-only --no-align --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
      interval: 5m
      start_interval: 30s
      start_period: 5m
@@ -41,7 +41,7 @@ services:
  redis:
    container_name: immich_redis
-    image: redis:6.2-alpine@sha256:e31ca60b18f7e9b78b573d156702471d4eda038803c0b8e6f01559f350031e93
+    image: redis:6.2-alpine@sha256:d6c2911ac51b289db208767581a5d154544f2b2fe4914ea5056443f62dc6e900
    healthcheck:
      test: redis-cli ping || exit 1
    restart: always
@@ -61,7 +61,7 @@ services:
    ports:
      - 5432:5432
    healthcheck:
-      test: pg_isready --dbname='${DB_DATABASE_NAME}' || exit 1; Chksum="$$(psql --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' --tuples-only --no-align --command='SELECT SUM(checksum_failures) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
+      test: pg_isready --dbname='${DB_DATABASE_NAME}' || exit 1; Chksum="$$(psql --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' --tuples-only --no-align --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
      interval: 5m
      start_interval: 30s
      start_period: 5m
@@ -85,7 +85,7 @@ services:
    command: ['./run.sh', '-disable-reporting']
    ports:
      - 3000:3000
-    image: grafana/grafana:11.0.0-ubuntu@sha256:02e99d1ee0b52dc9d3000c7b5314e7a07e0dfd69cc49bb3f8ce323491ed3406b
+    image: grafana/grafana:11.0.0-ubuntu@sha256:dcd3ae78713958a862732c3608d32c03f0c279c35a2032d74b80b12c5cdc47b8
    volumes:
      - grafana-data:/var/lib/grafana
@@ -43,7 +43,7 @@ services:
  redis:
    container_name: immich_redis
-    image: docker.io/redis:6.2-alpine@sha256:e31ca60b18f7e9b78b573d156702471d4eda038803c0b8e6f01559f350031e93
+    image: docker.io/redis:6.2-alpine@sha256:d6c2911ac51b289db208767581a5d154544f2b2fe4914ea5056443f62dc6e900
    healthcheck:
      test: redis-cli ping || exit 1
    restart: always
@@ -59,7 +59,7 @@ services:
    volumes:
      - ${DB_DATA_LOCATION}:/var/lib/postgresql/data
    healthcheck:
-      test: pg_isready --dbname='${DB_DATABASE_NAME}' || exit 1; Chksum="$$(psql --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' --tuples-only --no-align --command='SELECT SUM(checksum_failures) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
+      test: pg_isready --dbname='${DB_DATABASE_NAME}' || exit 1; Chksum="$$(psql --dbname='${DB_DATABASE_NAME}' --username='${DB_USERNAME}' --tuples-only --no-align --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1
      interval: 5m
      start_interval: 30s
      start_period: 5m
@@ -3,10 +3,10 @@ global:
  evaluation_interval: 15s
 scrape_configs:
-  - job_name: immich_server
+  - job_name: immich_api
    static_configs:
      - targets: ['immich-server:8081']
  - job_name: immich_microservices
    static_configs:
-      - targets: ['immich-microservices:8081']
+      - targets: ['immich-server:8082']
@@ -0,0 +1,49 @@
 #!/bin/sh
 set -eu
 LOG_LEVEL="${IMMICH_LOG_LEVEL:='info'}"
 logDebug() {
    if [ "$LOG_LEVEL" = "debug" ] || [ "$LOG_LEVEL" = "verbose" ]; then
        echo "DEBUG: $1" >&2
    fi
 }
 if [ -f /sys/fs/cgroup/cgroup.controllers ]; then
    logDebug "cgroup v2 detected."
    if [ -f /sys/fs/cgroup/cpu.max ]; then
        read -r quota period </sys/fs/cgroup/cpu.max
        if [ "$quota" = "max" ]; then
            logDebug "No CPU limits set."
            unset quota period
        fi
    else
        logDebug "/sys/fs/cgroup/cpu.max not found."
    fi
 else
    logDebug "cgroup v1 detected."
    if [ -f /sys/fs/cgroup/cpu/cpu.cfs_quota_us ] && [ -f /sys/fs/cgroup/cpu/cpu.cfs_period_us ]; then
        quota=$(cat /sys/fs/cgroup/cpu/cpu.cfs_quota_us)
        period=$(cat /sys/fs/cgroup/cpu/cpu.cfs_period_us)
        if [ "$quota" = "-1" ]; then
            logDebug "No CPU limits set."
            unset quota period
        fi
    else
        logDebug "/sys/fs/cgroup/cpu/cpu.cfs_quota_us or /sys/fs/cgroup/cpu/cpu.cfs_period_us not found."
    fi
 fi
 if [ -n "${quota:-}" ] && [ -n "${period:-}" ]; then
    cpus=$((quota / period))
    if [ "$cpus" -eq 0 ]; then
        cpus=1
    fi
 else
    cpus=$(grep -c ^processor /proc/cpuinfo)
 fi
 echo "$cpus"
@@ -1 +1 @@
-20.13
+20.14
@@ -0,0 +1,23 @@
 # Email Notifications
 Immich supports the option to send notifications via Email for the following events:
 - Creating a new user
 - Notifying a user when they get added to a shared album
 - Informing other users about the addition of new assets to a shared album
 ## SMTP settings
 You can access the settings panel from the web at `Administration -> Settings -> Notification settings`
 Under Email, enter the following details to connect with SMTP servers.
 You can use the following [guide](/docs/guides/smtp-gmail) to use Gmail's SMTP server.
 <img src={require('./img/email-settings.png').default} width="80%" title="SMTP settings" />
 ## User's notifications settings
 Users can manage their email notification settings from their account settings page on the web. They can choose to turn email notifications on or off for the following events:
 <img src={require('./img/user-notifications-settings.png').default} width="80%" title="User notification settings" />
@@ -117,7 +117,27 @@ Immich has a route (`/api/oauth/mobile-redirect`) that is already configured to
 Here's an example of OAuth configured for Authentik:
-<img src={require('./img/oauth-settings.png').default} title="OAuth settings" />
+Configuration of Authorised redirect URIs (Authentik OAuth2/OpenID Provider)
 <img src={require('./img/authentik-redirect-uris-example.webp').default} width='70%' title="Authentik authorised redirect URIs" />
 Configuration of OAuth in Immich System Settings
 | Setting                      | Value                                                                              |
 | ---------------------------- | ---------------------------------------------------------------------------------- |
 | Issuer URL                   | `https://example.immich.app/application/o/immich/.well-known/openid-configuration` |
 | Client ID                    | AFCj2rM1f4rps**\*\*\*\***\***\*\*\*\***lCLEum6hH9...                               |
 | Client Secret                | 0v89FXkQOWO\***\*\*\*\*\***\*\*\***\*\*\*\*\***mprbvXD549HH6s1iw...                |
 | Scope                        | openid email profile                                                               |
 | Signing Algorithm            | RS256                                                                              |
 | Storage Label Claim          | preferred_username                                                                 |
 | Storage Quota Claim          | immich_quota                                                                       |
 | Default Storage Quota (GiB)  | 0 (0 for unlimited quota)                                                          |
 | Button Text                  | Sign in with Authentik (optional)                                                  |
 | Auto Register                | Enabled (optional)                                                                 |
 | Auto Launch                  | Enabled (optional)                                                                 |
 | Mobile Redirect URI Override | Disable                                                                            |
 | Mobile Redirect URI          |                                                                                    |
 </details>
@@ -126,11 +146,13 @@ Here's an example of OAuth configured for Authentik:
 ### Google Example
 Here's an example of OAuth configured for Google:
 Configuration of Authorised redirect URIs (Google Console)
-<img src={require('./img/google-example.webp').default} width='50%' title="Authorised redirect URIs" />
+<img src={require('./img/google-redirect-uris-example.webp').default} width='50%' title="Google authorised redirect URIs" />
-Configuration of OAuth in System Settings
+Configuration of OAuth in Immich System Settings
 | Setting                      | Value                                                                                                  |
 | ---------------------------- | ------------------------------------------------------------------------------------------------------ |
@@ -10,6 +10,59 @@ Viewing and modifying the system settings is restricted to the Administrator.
 You can always return to the default settings by clicking the `Reset to default` button.
 :::
 ## Authentication Settings
 Manage password, OAuth, and other authentication settings
 ### 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.
 :::
 ## Image Settings (thumbnails and previews)
 - Thumbnails - Used in the main timeline.
 - Previews - Used in the asset viewer.
 By default Immich creates 3 thumbnails for each asset,
 Blurred (thumbhash) , Small - thumbnails (webp) , and Large - previews (jpeg/webp), using these settings you can change the quality for the thumbnails and previews files that are created.
 **Thumbnail format**  
 Allows you to choose the type of format you want for the Thumbnail images, Webp produces smaller files than jpeg, but is slower to encode.
 :::tip
 You can read in detail about the advantages and disadvantages of using webp over jpeg on [Adobe's website](https://www.adobe.com/creativecloud/file-types/image/raster/webp-file.html)
 :::
 **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.
 **Preview format**  
 Allows you to choose the type of format you want for the Preview images, Webp produces smaller files than jpeg, but is slower to encode.
 **Preview 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**  
 Image quality from 1-100. Higher is better for quality but produces larger files, this option affects the Preview and Thumbnail images.
 **Prefer wide gamut**  
 Use Display P3 for thumbnails. This better preserves the vibrance of images with wide colorspaces, but images may appear differently on old devices with an old browser version. sRGB images are kept as sRGB to avoid color shifts.
 **Prefer embedded preview**  
 Use embedded previews in RAW photos as the input to image processing when available. This can produce more accurate colors for some images, but the quality of the preview is camera-dependent and the image may have more compression artifacts.
 :::tip
 The default resolution for Large thumbnails can be lowered from 1440p (default) to 1080p or 720p to save storage space.
 :::
 ## 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.
@@ -19,6 +72,11 @@ this advice improves throughput, not latency, for example, it will make Smart Se
 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.
 :::danger IMPORTANT
 If you increase the concurrency from the defaults we set, especially for thumbnail generation, make sure you do not increase them past the amount of CPU cores you have available.
 Doing so can impact API responsiveness with no gain in thumbnail generation speed.
 :::
 :::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.
@@ -87,17 +145,9 @@ The map can be adjusted via [OpenMapTiles](https://openmaptiles.org/styles/) for
 Immich supports [Reverse Geocoding](/docs/features/reverse-geocoding) using data from the [GeoNames](https://www.geonames.org/) geographical database.
-## OAuth Authentication
+## Notification Settings
-Immich supports OAuth Authentication. Read more about this feature and its configuration [here](/docs/administration/oauth).
+SMTP server setup, for user creation notifications, new albums, etc. More information can be found [here](/docs/administration/email-notification)
 ## 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
@@ -125,27 +175,6 @@ p {
 }
 ```
 ## 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.
@@ -13,6 +13,20 @@ Immich supports multiple users, each with their own library.
 <UserCreate />
 ## Send new user email notification
 :::note
 This option is only available if an SMTP server has been configured in the administrator settings.
 :::
 Admin can send a welcome email if the Email option is set, you can learn here how to set up the SMTP server in Immich.
 <img
  src={require('./img/send-user-email-notification.webp').default}
  width="40%"
  title="Send user email notification"
 />
 ## Set Storage Quota For 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.
@@ -60,17 +60,17 @@ For RKMPP to work:
 #### Basic Setup
 1. If you do not already have it, download the latest [`hwaccel.transcoding.yml`][hw-file] file and ensure it's in the same folder as the `docker-compose.yml`.
-2. In the `docker-compose.yml` under `immich-microservices`, uncomment the `extends` section and change `cpu` to the appropriate backend.
+2. In the `docker-compose.yml` under `immich-server`, uncomment the `extends` section and change `cpu` to the appropriate backend.
 - For VAAPI on WSL2, be sure to use `vaapi-wsl` rather than `vaapi`
-3. Redeploy the `immich-microservices` container with these updated settings.
+3. Redeploy the `immich-server` container with these updated settings.
 4. In the Admin page under `Video transcoding settings`, change the hardware acceleration setting to the appropriate option and save.
 5. (Optional) If using a compatible backend, you may enable hardware decoding for optimal performance.
 #### Single Compose File
-Some platforms, including Unraid and Portainer, do not support multiple Compose files as of writing. As an alternative, you can "inline" the relevant contents of the [`hwaccel.transcoding.yml`][hw-file] file into the `immich-microservices` service directly.
+Some platforms, including Unraid and Portainer, do not support multiple Compose files as of writing. As an alternative, you can "inline" the relevant contents of the [`hwaccel.transcoding.yml`][hw-file] file into the `immich-server` service directly.
 For example, the `qsv` section in this file is:
@@ -79,21 +79,22 @@ devices:
  - /dev/dri:/dev/dri
 ```
-You can add this to the `immich-microservices` service instead of extending from `hwaccel.transcoding.yml`:
+You can add this to the `immich-server` service instead of extending from `hwaccel.transcoding.yml`:
 ```yaml
-immich-microservices:
+immich-server:
-  container_name: immich_microservices
+  container_name: immich_server
  image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
  # Note the lack of an `extends` section
  devices:
    - /dev/dri:/dev/dri
  command: ['start.sh', 'microservices']
  volumes:
    - ${UPLOAD_LOCATION}:/usr/src/app/upload
    - /etc/localtime:/etc/localtime:ro
  env_file:
    - .env
  ports:
    - 2283:3001
  depends_on:
    - redis
    - database
@@ -0,0 +1,20 @@
 # SMTP settings using Gmail
 This guide walks you through how to get the information you need to set up your Immich instance to send emails using Gmail's SMTP server.
 ## Create an app password
 From your Google account settings
 - Add [2-Step Verification](https://support.google.com/accounts/answer/185839) to your Google account (Required)
 - [Create an app password](https://myaccount.google.com/apppasswords).
 At the end of creating your app passwords, a password will be displayed; save it, it will be used for the password field when setting up the SMTP server in Immich.
 <img src={require('./img/google-app-password.webp').default} title="Authorised redirect URIs" />
 ## Entering the SMTP credential in Immich
 Entering your credential in Immich's email notification settings at `Administration -> Settings -> Notification Settings`
 <img src={require('./img/email-settings.png').default} width="80%" title="SMTP settings" />
@@ -38,16 +38,19 @@ Regardless of filesystem, it is not recommended to use a network share for your
 ## General
-| Variable                        | Description                                     |         Default          | Containers               | Workers            |
+| Variable                            | Description                                     |           Default            | Containers               | Workers            |
-| :------------------------------ | :---------------------------------------------- | :----------------------: | :----------------------- | :----------------- |
+| :---------------------------------- | :---------------------------------------------- | :--------------------------: | :----------------------- | :----------------- |
-| `TZ`                            | Timezone                                        |                          | server                   | microservices      |
+| `TZ`                                | Timezone                                        |                              | server                   | microservices      |
-| `IMMICH_ENV`                    | Environment (production, development)           |       `production`       | server, machine learning | api, microservices |
+| `IMMICH_ENV`                        | Environment (production, development)           |         `production`         | server, machine learning | api, microservices |
-| `IMMICH_LOG_LEVEL`              | Log Level (verbose, debug, log, warn, error)    |          `log`           | server, machine learning | api, microservices |
+| `IMMICH_LOG_LEVEL`                  | Log Level (verbose, debug, log, warn, error)    |            `log`             | server, machine learning | api, microservices |
-| `IMMICH_MEDIA_LOCATION`         | Media Location                                  | `./upload`<sup>\*1</sup> | server                   | api, microservices |
+| `IMMICH_MEDIA_LOCATION`             | Media Location                                  |   `./upload`<sup>\*1</sup>   | server                   | api, microservices |
-| `IMMICH_CONFIG_FILE`            | Path to config file                             |                          | server                   | api, microservices |
+| `IMMICH_CONFIG_FILE`                | Path to config file                             |                              | server                   | api, microservices |
-| `IMMICH_WEB_ROOT`               | Path of root index.html                         |    `/usr/src/app/www`    | server                   | api                |
+| `IMMICH_WEB_ROOT`                   | Path of root index.html                         |      `/usr/src/app/www`      | server                   | api                |
-| `IMMICH_REVERSE_GEOCODING_ROOT` | Path of reverse geocoding dump directory        |   `/usr/src/resources`   | server                   | microservices      |
+| `IMMICH_REVERSE_GEOCODING_ROOT`     | Path of reverse geocoding dump directory        |     `/usr/src/resources`     | server                   | microservices      |
-| `NO_COLOR`                      | Set to `true` to disable color-coded log output |         `false`          | server, machine learning |                    |
+| `NO_COLOR`                          | Set to `true` to disable color-coded log output |           `false`            | server, machine learning |                    |
 | `CPU_CORES`                         | Amount of cores available to the immich server  | auto-detected cpu core count | server                   |                    |
 | `IMMICH_API_METRICS_PORT`           | Port for the OTEL metrics                       |            `8081`            | server                   | api                |
 | `IMMICH_MICROSERVICES_METRICS_PORT` | Port for the OTEL metrics                       |            `8082`            | server                   | microservices      |
 \*1: With the default `WORKDIR` of `/usr/src/app`, this path will resolve to `/usr/src/app/upload`.
 It only need to be set if the Immich deployment method is changing.
@@ -94,6 +94,10 @@ const config = {
          srcDark: 'img/immich-logo-inline-dark.png',
        },
        items: [
          {
            type: 'custom-versionSwitcher',
            position: 'right',
          },
          {
            to: '/docs/overview/introduction',
            position: 'right',
@@ -56,6 +56,6 @@
    "node": ">=20"
  },
  "volta": {
-    "node": "20.13.1"
+    "node": "20.14.0"
  }
 }
@@ -0,0 +1,59 @@
 import '@docusaurus/theme-classic/lib/theme/Unlisted/index';
 import { useWindowSize } from '@docusaurus/theme-common';
 import DropdownNavbarItem from '@theme/NavbarItem/DropdownNavbarItem';
 import React, { useEffect, useState } from 'react';
 export default function VersionSwitcher(): JSX.Element {
  const [versions, setVersions] = useState([]);
  const [label, setLabel] = useState('Versions');
  const windowSize = useWindowSize();
  useEffect(() => {
    async function getVersions() {
      try {
        let baseUrl = 'https://immich.app';
        if (window.location.origin === 'http://localhost:3005') {
          baseUrl = window.location.origin;
        }
        const response = await fetch(`${baseUrl}/archived-versions.json`);
        const archiveVersions = await response.json();
        const allVersions = [
          { label: 'Next', url: 'https://main.preview.immich.app' },
          { label: 'Latest', url: 'https://immich.app' },
          ...archiveVersions,
        ];
        setVersions(allVersions);
        const activeVersion = allVersions.find((version) => new URL(version.url).origin === window.location.origin);
        if (activeVersion) {
          setLabel(activeVersion.label);
        }
      } catch (error) {
        console.error('Failed to fetch versions', error);
      }
    }
    if (versions.length === 0) {
      getVersions();
    }
  }, []);
  return (
    versions.length > 0 && (
      <DropdownNavbarItem
        className="navbar__item"
        label={label}
        mobile={windowSize === 'mobile'}
        items={versions.map(({ label, url }) => ({
          label,
          to: url,
          target: '_self',
        }))}
      />
    )
  );
 }
@@ -15,6 +15,10 @@ button {
  font-family: 'Overpass', sans-serif;
 }
 img {
  border-radius: 15px;
 }
 /* You can override the default Infima variables here. */
 :root {
  --ifm-color-primary: #4250af;
@@ -63,12 +63,14 @@ import {
  mdiVectorCombine,
  mdiVideo,
  mdiWeb,
  mdiContentDuplicate,
 } from '@mdi/js';
 import Layout from '@theme/Layout';
 import React from 'react';
 import { Item, Timeline } from '../components/timeline';
 const releases = {
  'v1.106.0': new Date(2024, 5, 11),
  'v1.104.0': new Date(2024, 4, 13),
  'v1.103.0': new Date(2024, 3, 29),
  'v1.102.0': new Date(2024, 3, 15),
@@ -216,13 +218,19 @@ const roadmap: Item[] = [
 ];
 const milestones: Item[] = [
-  // withRelease({
+  withRelease({
-  //   icon: mdiVectorCombine,
+    icon: mdiContentDuplicate,
-  //   title: 'Container consolidation',
+    title: 'Similar image detection',
-  //   description:
+    description: 'Detect duplicate assets that aren’t exactly identical',
-  //     'The microservices container can be run as a worker within the server image, allowing us to remove it from the default stack.',
+    release: 'v1.106.0',
-  //   release: 'v1.106.0',
+  }),
-  // }),
+  withRelease({
    icon: mdiVectorCombine,
    title: 'Container consolidation',
    description:
      'The microservices container can be run as a worker within the server image, allowing us to remove it from the default stack.',
    release: 'v1.106.0',
  }),
  withRelease({
    icon: mdiPencil,
    iconColor: 'saddlebrown',
@@ -0,0 +1,7 @@
 import ComponentTypes from '@theme-original/NavbarItem/ComponentTypes';
 import VersionSwitcher from '@site/src/components/version-switcher';
 export default {
  ...ComponentTypes,
  'custom-versionSwitcher': VersionSwitcher,
 };
@@ -0,0 +1,58 @@
 [
  {
    "label": "v1.106.3",
    "url": "https://v1.106.3.archive.immich.app"
  },
  {
    "label": "v1.106.2",
    "url": "https://v1.106.2.archive.immich.app"
  },
  {
    "label": "v1.106.1",
    "url": "https://v1.106.1.archive.immich.app"
  },
  {
    "label": "v1.105.1",
    "url": "https://v1.105.1.archive.immich.app/"
  },
  {
    "label": "v1.105.0",
    "url": "https://v1.105.0.archive.immich.app/"
  },
  {
    "label": "v1.104.0",
    "url": "https://v1.104.0.archive.immich.app/"
  },
  {
    "label": "v1.103.1",
    "url": "https://v1.103.1.archive.immich.app/"
  },
  {
    "label": "v1.103.0",
    "url": "https://v1.103.0.archive.immich.app/"
  },
  {
    "label": "v1.102.3",
    "url": "https://v1.102.3.archive.immich.app/"
  },
  {
    "label": "v1.102.2",
    "url": "https://v1.102.2.archive.immich.app/"
  },
  {
    "label": "v1.102.1",
    "url": "https://v1.102.1.archive.immich.app/"
  },
  {
    "label": "v1.102.0",
    "url": "https://v1.102.0.archive.immich.app/"
  },
  {
    "label": "v1.101.0",
    "url": "https://v1.101.0.archive.immich.app/"
  },
  {
    "label": "v1.100.0",
    "url": "https://v1.100.0.archive.immich.app/"
  }
 ]
@@ -1 +1 @@
-20.13
+20.14
@@ -27,7 +27,7 @@ services:
      - 2283:3001
  redis:
-    image: redis:6.2-alpine@sha256:e31ca60b18f7e9b78b573d156702471d4eda038803c0b8e6f01559f350031e93
+    image: redis:6.2-alpine@sha256:d6c2911ac51b289db208767581a5d154544f2b2fe4914ea5056443f62dc6e900
  database:
    image: tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
@@ -1,12 +1,12 @@
 {
  "name": "immich-e2e",
-  "version": "1.105.1",
+  "version": "1.106.3",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "immich-e2e",
-      "version": "1.105.1",
+      "version": "1.106.3",
      "license": "GNU Affero General Public License version 3",
      "devDependencies": {
        "@immich/cli": "file:../cli",
@@ -39,7 +39,7 @@
    },
    "../cli": {
      "name": "@immich/cli",
-      "version": "2.2.0",
+      "version": "2.2.3",
      "dev": true,
      "license": "GNU Affero General Public License version 3",
      "dependencies": {
@@ -81,7 +81,7 @@
    },
    "../open-api/typescript-sdk": {
      "name": "@immich/sdk",
-      "version": "1.105.1",
+      "version": "1.106.3",
      "dev": true,
      "license": "GNU Affero General Public License version 3",
      "dependencies": {
@@ -1230,9 +1230,9 @@
      "dev": true
    },
    "node_modules/@types/node": {
-      "version": "20.12.12",
+      "version": "20.12.13",
-      "resolved": "https://registry.npmjs.org/@types/node/-/node-20.12.12.tgz",
+      "resolved": "https://registry.npmjs.org/@types/node/-/node-20.12.13.tgz",
-      "integrity": "sha512-eWLDGF/FOSPtAvEqeRAQ4C8LSA7M1I7i0ky1I8U7kD1J5ITyW3AsRhQrKVoWf5pFKZ2kILsEGJhsI9r93PYnOw==",
+      "integrity": "sha512-gBGeanV41c1L171rR7wjbMiEpEI/l5XFQdLLfhr/REwpgDy/4U8y89+i8kRiLzDyZdOkXh+cRaTetUnCYutoXA==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
@@ -1344,17 +1344,17 @@
      }
    },
    "node_modules/@typescript-eslint/eslint-plugin": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/eslint-plugin/-/eslint-plugin-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/eslint-plugin/-/eslint-plugin-7.11.0.tgz",
-      "integrity": "sha512-PzCr+a/KAef5ZawX7nbyNwBDtM1HdLIT53aSA2DDlxmxMngZ43O8SIePOeX8H5S+FHXeI6t97mTt/dDdzY4Fyw==",
+      "integrity": "sha512-P+qEahbgeHW4JQ/87FuItjBj8O3MYv5gELDzr8QaQ7fsll1gSMTYb6j87MYyxwf3DtD7uGFB9ShwgmCJB5KmaQ==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
        "@eslint-community/regexpp": "^4.10.0",
-        "@typescript-eslint/scope-manager": "7.10.0",
+        "@typescript-eslint/scope-manager": "7.11.0",
-        "@typescript-eslint/type-utils": "7.10.0",
+        "@typescript-eslint/type-utils": "7.11.0",
-        "@typescript-eslint/utils": "7.10.0",
+        "@typescript-eslint/utils": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0",
+        "@typescript-eslint/visitor-keys": "7.11.0",
        "graphemer": "^1.4.0",
        "ignore": "^5.3.1",
        "natural-compare": "^1.4.0",
@@ -1378,16 +1378,16 @@
      }
    },
    "node_modules/@typescript-eslint/parser": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/parser/-/parser-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/parser/-/parser-7.11.0.tgz",
-      "integrity": "sha512-2EjZMA0LUW5V5tGQiaa2Gys+nKdfrn2xiTIBLR4fxmPmVSvgPcKNW+AE/ln9k0A4zDUti0J/GZXMDupQoI+e1w==",
+      "integrity": "sha512-yimw99teuaXVWsBcPO1Ais02kwJ1jmNA1KxE7ng0aT7ndr1pT1wqj0OJnsYVGKKlc4QJai86l/025L6z8CljOg==",
      "dev": true,
      "license": "BSD-2-Clause",
      "dependencies": {
-        "@typescript-eslint/scope-manager": "7.10.0",
+        "@typescript-eslint/scope-manager": "7.11.0",
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/typescript-estree": "7.10.0",
+        "@typescript-eslint/typescript-estree": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0",
+        "@typescript-eslint/visitor-keys": "7.11.0",
        "debug": "^4.3.4"
      },
      "engines": {
@@ -1407,14 +1407,14 @@
      }
    },
    "node_modules/@typescript-eslint/scope-manager": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/scope-manager/-/scope-manager-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/scope-manager/-/scope-manager-7.11.0.tgz",
-      "integrity": "sha512-7L01/K8W/VGl7noe2mgH0K7BE29Sq6KAbVmxurj8GGaPDZXPr8EEQ2seOeAS+mEV9DnzxBQB6ax6qQQ5C6P4xg==",
+      "integrity": "sha512-27tGdVEiutD4POirLZX4YzT180vevUURJl4wJGmm6TrQoiYwuxTIY98PBp6L2oN+JQxzE0URvYlzJaBHIekXAw==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0"
+        "@typescript-eslint/visitor-keys": "7.11.0"
      },
      "engines": {
        "node": "^18.18.0 || >=20.0.0"
@@ -1425,14 +1425,14 @@
      }
    },
    "node_modules/@typescript-eslint/type-utils": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/type-utils/-/type-utils-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/type-utils/-/type-utils-7.11.0.tgz",
-      "integrity": "sha512-D7tS4WDkJWrVkuzgm90qYw9RdgBcrWmbbRkrLA4d7Pg3w0ttVGDsvYGV19SH8gPR5L7OtcN5J1hTtyenO9xE9g==",
+      "integrity": "sha512-WmppUEgYy+y1NTseNMJ6mCFxt03/7jTOy08bcg7bxJJdsM4nuhnchyBbE8vryveaJUf62noH7LodPSo5Z0WUCg==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
-        "@typescript-eslint/typescript-estree": "7.10.0",
+        "@typescript-eslint/typescript-estree": "7.11.0",
-        "@typescript-eslint/utils": "7.10.0",
+        "@typescript-eslint/utils": "7.11.0",
        "debug": "^4.3.4",
        "ts-api-utils": "^1.3.0"
      },
@@ -1453,9 +1453,9 @@
      }
    },
    "node_modules/@typescript-eslint/types": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/types/-/types-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/types/-/types-7.11.0.tgz",
-      "integrity": "sha512-7fNj+Ya35aNyhuqrA1E/VayQX9Elwr8NKZ4WueClR3KwJ7Xx9jcCdOrLW04h51de/+gNbyFMs+IDxh5xIwfbNg==",
+      "integrity": "sha512-MPEsDRZTyCiXkD4vd3zywDCifi7tatc4K37KqTprCvaXptP7Xlpdw0NR2hRJTetG5TxbWDB79Ys4kLmHliEo/w==",
      "dev": true,
      "license": "MIT",
      "engines": {
@@ -1467,14 +1467,14 @@
      }
    },
    "node_modules/@typescript-eslint/typescript-estree": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/typescript-estree/-/typescript-estree-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/typescript-estree/-/typescript-estree-7.11.0.tgz",
-      "integrity": "sha512-LXFnQJjL9XIcxeVfqmNj60YhatpRLt6UhdlFwAkjNc6jSUlK8zQOl1oktAP8PlWFzPQC1jny/8Bai3/HPuvN5g==",
+      "integrity": "sha512-cxkhZ2C/iyi3/6U9EPc5y+a6csqHItndvN/CzbNXTNrsC3/ASoYQZEt9uMaEp+xFNjasqQyszp5TumAVKKvJeQ==",
      "dev": true,
      "license": "BSD-2-Clause",
      "dependencies": {
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/visitor-keys": "7.10.0",
+        "@typescript-eslint/visitor-keys": "7.11.0",
        "debug": "^4.3.4",
        "globby": "^11.1.0",
        "is-glob": "^4.0.3",
@@ -1522,16 +1522,16 @@
      }
    },
    "node_modules/@typescript-eslint/utils": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/utils/-/utils-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/utils/-/utils-7.11.0.tgz",
-      "integrity": "sha512-olzif1Fuo8R8m/qKkzJqT7qwy16CzPRWBvERS0uvyc+DHd8AKbO4Jb7kpAvVzMmZm8TrHnI7hvjN4I05zow+tg==",
+      "integrity": "sha512-xlAWwPleNRHwF37AhrZurOxA1wyXowW4PqVXZVUNCLjB48CqdPJoJWkrpH2nij9Q3Lb7rtWindtoXwxjxlKKCA==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
        "@eslint-community/eslint-utils": "^4.4.0",
-        "@typescript-eslint/scope-manager": "7.10.0",
+        "@typescript-eslint/scope-manager": "7.11.0",
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
-        "@typescript-eslint/typescript-estree": "7.10.0"
+        "@typescript-eslint/typescript-estree": "7.11.0"
      },
      "engines": {
        "node": "^18.18.0 || >=20.0.0"
@@ -1545,13 +1545,13 @@
      }
    },
    "node_modules/@typescript-eslint/visitor-keys": {
-      "version": "7.10.0",
+      "version": "7.11.0",
-      "resolved": "https://registry.npmjs.org/@typescript-eslint/visitor-keys/-/visitor-keys-7.10.0.tgz",
+      "resolved": "https://registry.npmjs.org/@typescript-eslint/visitor-keys/-/visitor-keys-7.11.0.tgz",
-      "integrity": "sha512-9ntIVgsi6gg6FIq9xjEO4VQJvwOqA3jaBFQJ/6TK5AvEup2+cECI6Fh7QiBxmfMHXU0V0J4RyPeOU1VDNzl9cg==",
+      "integrity": "sha512-7syYk4MzjxTEk0g/w3iqtgxnFQspDJfn6QKD36xMuuhTzjcxY7F8EmBLnALjVyaOF1/bVocu3bS/2/F7rXrveQ==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
-        "@typescript-eslint/types": "7.10.0",
+        "@typescript-eslint/types": "7.11.0",
        "eslint-visitor-keys": "^3.4.3"
      },
      "engines": {
@@ -2700,10 +2700,11 @@
      }
    },
    "node_modules/exiftool-vendored": {
-      "version": "26.0.0",
+      "version": "26.1.0",
-      "resolved": "https://registry.npmjs.org/exiftool-vendored/-/exiftool-vendored-26.0.0.tgz",
+      "resolved": "https://registry.npmjs.org/exiftool-vendored/-/exiftool-vendored-26.1.0.tgz",
-      "integrity": "sha512-2TRxx21ovD95VvdSzHb/sTYYcwhiizQIhhVAbrgua9KoL902QRieREGvaUtfBZNjsptdjonuyku2kUBJCPqsgw==",
+      "integrity": "sha512-Bhy2Ia86Agt3+PbJJhWeVMqJNXl74XJ0Oygef5F5uCL13fTxlmF8dECHiChyx8bBc3sxIw+2Q3ehWunJh3bs6w==",
      "dev": true,
      "license": "MIT",
      "dependencies": {
        "@photostructure/tz-lookup": "^10.0.0",
        "@types/luxon": "^3.4.2",
@@ -2712,25 +2713,27 @@
        "luxon": "^3.4.4"
      },
      "optionalDependencies": {
-        "exiftool-vendored.exe": "12.84.0",
+        "exiftool-vendored.exe": "12.85.0",
-        "exiftool-vendored.pl": "12.84.0"
+        "exiftool-vendored.pl": "12.85.0"
      }
    },
    "node_modules/exiftool-vendored.exe": {
-      "version": "12.84.0",
+      "version": "12.85.0",
-      "resolved": "https://registry.npmjs.org/exiftool-vendored.exe/-/exiftool-vendored.exe-12.84.0.tgz",
+      "resolved": "https://registry.npmjs.org/exiftool-vendored.exe/-/exiftool-vendored.exe-12.85.0.tgz",
-      "integrity": "sha512-9ocqJb0Pr9k0TownEMd75payF/XOQLF/swr/l0Ep49D+m609uIZsW09CtowhXmk1KrIFobS3+SkdXK04CSyUwQ==",
+      "integrity": "sha512-rWsKVp9oXsS79S3bfCNXKeEo4av0xcd7slk/TfPpCa5pojg8ZVXSVfPZMAAlhOuK63YXrKN/e3jRNReeGP+2Gw==",
      "dev": true,
      "license": "MIT",
      "optional": true,
      "os": [
        "win32"
      ]
    },
    "node_modules/exiftool-vendored.pl": {
-      "version": "12.84.0",
+      "version": "12.85.0",
-      "resolved": "https://registry.npmjs.org/exiftool-vendored.pl/-/exiftool-vendored.pl-12.84.0.tgz",
+      "resolved": "https://registry.npmjs.org/exiftool-vendored.pl/-/exiftool-vendored.pl-12.85.0.tgz",
-      "integrity": "sha512-TxvMRaVYtd24Vupn48zy24LOYItIIWEu4dgt/VlqLwxQItTpvJTV9YH04iZRvaNh9ZdPRgVKWMuuUDBBHv+lAg==",
+      "integrity": "sha512-AelZQCCfl0a0g7PYx90TqbNGlSu2zDbRfCTjGw6bBBYnJF0NUfUWVhTpa8XGe2lHx1KYikH8AkJaey3esAxMAg==",
      "dev": true,
      "license": "MIT",
      "optional": true,
      "os": [
        "!win32"
@@ -1,6 +1,6 @@
 {
  "name": "immich-e2e",
-  "version": "1.105.1",
+  "version": "1.106.3",
  "description": "",
  "main": "index.js",
  "type": "module",
@@ -47,6 +47,6 @@
    "vitest": "^1.3.0"
  },
  "volta": {
-    "node": "20.13.1"
+    "node": "20.14.0"
  }
 }
@@ -1148,4 +1148,29 @@ describe('/asset', () => {
      expect(video.checksum).toStrictEqual(checksum);
    });
  });
  describe('POST /assets/exist', () => {
    it('ignores invalid deviceAssetIds', async () => {
      const response = await utils.checkExistingAssets(user1.accessToken, {
        deviceId: 'test-assets-exist',
        deviceAssetIds: ['invalid', 'INVALID'],
      });
      expect(response.existingIds).toHaveLength(0);
    });
    it('returns the IDs of existing assets', async () => {
      await utils.createAsset(user1.accessToken, {
        deviceId: 'test-assets-exist',
        deviceAssetId: 'test-asset-0',
      });
      const response = await utils.checkExistingAssets(user1.accessToken, {
        deviceId: 'test-assets-exist',
        deviceAssetIds: ['test-asset-0'],
      });
      expect(response.existingIds).toEqual(['test-asset-0']);
    });
  });
 });
@@ -1,4 +1,11 @@
-import { LibraryResponseDto, LoginResponseDto, ScanLibraryDto, getAllLibraries, scanLibrary } from '@immich/sdk';
+import {
  LibraryResponseDto,
  LoginResponseDto,
  ScanLibraryDto,
  getAllLibraries,
  removeOfflineFiles,
  scanLibrary,
 } from '@immich/sdk';
 import { cpSync, existsSync } from 'node:fs';
 import { Socket } from 'socket.io-client';
 import { userDto, uuidDto } from 'src/fixtures';
@@ -384,6 +391,51 @@ describe('/libraries', () => {
      );
    });
    it('should not try to delete offline files', async () => {
      utils.createImageFile(`${testAssetDir}/temp/offline1/assetA.png`);
      const library = await utils.createLibrary(admin.accessToken, {
        ownerId: admin.userId,
        importPaths: [`${testAssetDirInternal}/temp/offline1`],
      });
      await scan(admin.accessToken, library.id);
      await utils.waitForQueueFinish(admin.accessToken, 'library');
      const { assets: initialAssets } = await utils.metadataSearch(admin.accessToken, { libraryId: library.id });
      expect(initialAssets).toEqual({
        count: 1,
        total: 1,
        facets: [],
        items: [expect.objectContaining({ originalFileName: 'assetA.png' })],
        nextPage: null,
      });
      utils.removeImageFile(`${testAssetDir}/temp/offline1/assetA.png`);
      await scan(admin.accessToken, library.id);
      await utils.waitForQueueFinish(admin.accessToken, 'library');
      const { assets: offlineAssets } = await utils.metadataSearch(admin.accessToken, {
        libraryId: library.id,
        isOffline: true,
      });
      expect(offlineAssets).toEqual({
        count: 1,
        total: 1,
        facets: [],
        items: [expect.objectContaining({ originalFileName: 'assetA.png' })],
        nextPage: null,
      });
      utils.createImageFile(`${testAssetDir}/temp/offline1/assetA.png`);
      await removeOfflineFiles({ id: library.id }, { headers: asBearerAuth(admin.accessToken) });
      await utils.waitForQueueFinish(admin.accessToken, 'library');
      await utils.waitForWebsocketEvent({ event: 'assetDelete', total: 1 });
      expect(existsSync(`${testAssetDir}/temp/offline1/assetA.png`)).toBe(true);
    });
    it('should scan new files', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
        ownerId: admin.userId,
@@ -507,10 +559,10 @@ describe('/libraries', () => {
    it('should remove offline files', async () => {
      const library = await utils.createLibrary(admin.accessToken, {
        ownerId: admin.userId,
-        importPaths: [`${testAssetDirInternal}/temp`],
+        importPaths: [`${testAssetDirInternal}/temp/offline2`],
      });
-      utils.createImageFile(`${testAssetDir}/temp/directoryA/assetB.png`);
+      utils.createImageFile(`${testAssetDir}/temp/offline2/assetA.png`);
      await scan(admin.accessToken, library.id);
      await utils.waitForQueueFinish(admin.accessToken, 'library');
@@ -518,9 +570,9 @@ describe('/libraries', () => {
      const { assets: initialAssets } = await utils.metadataSearch(admin.accessToken, {
        libraryId: library.id,
      });
-      expect(initialAssets.count).toBe(3);
+      expect(initialAssets.count).toBe(1);
-      utils.removeImageFile(`${testAssetDir}/temp/directoryA/assetB.png`);
+      utils.removeImageFile(`${testAssetDir}/temp/offline2/assetA.png`);
      await scan(admin.accessToken, library.id);
      await utils.waitForQueueFinish(admin.accessToken, 'library');
@@ -541,7 +593,7 @@ describe('/libraries', () => {
      const { assets } = await utils.metadataSearch(admin.accessToken, { libraryId: library.id });
-      expect(assets.count).toBe(2);
+      expect(assets.count).toBe(0);
    });
    it('should not remove online files', async () => {
@@ -250,10 +250,18 @@ describe('/admin/users', () => {
        .set('Authorization', `Bearer ${admin.accessToken}`);
      expect(status).toBe(200);
-      expect(body).toEqual({ avatar: { color: 'orange' }, memories: { enabled: false } });
+      expect(body).toEqual({
        avatar: { color: 'orange' },
        memories: { enabled: false },
        emailNotifications: { enabled: true, albumInvite: true, albumUpdate: true },
      });
      const after = await getUserPreferencesAdmin({ id: admin.userId }, { headers: asBearerAuth(admin.accessToken) });
-      expect(after).toEqual({ avatar: { color: 'orange' }, memories: { enabled: false } });
+      expect(after).toEqual({
        avatar: { color: 'orange' },
        memories: { enabled: false },
        emailNotifications: { enabled: true, albumInvite: true, albumUpdate: true },
      });
    });
  });
@@ -5,51 +5,61 @@ export const errorDto = {
    error: 'Unauthorized',
    statusCode: 401,
    message: 'Authentication required',
    correlationId: expect.any(String),
  },
  forbidden: {
    error: 'Forbidden',
    statusCode: 403,
    message: expect.any(String),
    correlationId: expect.any(String),
  },
  wrongPassword: {
    error: 'Bad Request',
    statusCode: 400,
    message: 'Wrong password',
    correlationId: expect.any(String),
  },
  invalidToken: {
    error: 'Unauthorized',
    statusCode: 401,
    message: 'Invalid user token',
    correlationId: expect.any(String),
  },
  invalidShareKey: {
    error: 'Unauthorized',
    statusCode: 401,
    message: 'Invalid share key',
    correlationId: expect.any(String),
  },
  invalidSharePassword: {
    error: 'Unauthorized',
    statusCode: 401,
    message: 'Invalid password',
    correlationId: expect.any(String),
  },
  badRequest: (message: any = null) => ({
    error: 'Bad Request',
    statusCode: 400,
    message: message ?? expect.anything(),
    correlationId: expect.any(String),
  }),
  noPermission: {
    error: 'Bad Request',
    statusCode: 400,
    message: expect.stringContaining('Not found or no'),
    correlationId: expect.any(String),
  },
  incorrectLogin: {
    error: 'Unauthorized',
    statusCode: 401,
    message: 'Incorrect email or password',
    correlationId: expect.any(String),
  },
  alreadyHasAdmin: {
    error: 'Bad Request',
    statusCode: 400,
    message: 'The server already has an admin',
    correlationId: expect.any(String),
  },
 };
@@ -3,6 +3,7 @@ import {
  AssetMediaCreateDto,
  AssetMediaResponseDto,
  AssetResponseDto,
  CheckExistingAssetsDto,
  CreateAlbumDto,
  CreateLibraryDto,
  MetadataSearchDto,
@@ -10,6 +11,7 @@ import {
  SharedLinkCreateDto,
  UserAdminCreateDto,
  ValidateLibraryDto,
  checkExistingAssets,
  createAlbum,
  createApiKey,
  createLibrary,
@@ -323,6 +325,40 @@ export const utils = {
    return body as AssetMediaResponseDto;
  },
  replaceAsset: async (
    accessToken: string,
    assetId: string,
    dto?: Partial<Omit<AssetMediaCreateDto, 'assetData'>> & { assetData?: AssetData },
  ) => {
    const _dto = {
      deviceAssetId: 'test-1',
      deviceId: 'test',
      fileCreatedAt: new Date().toISOString(),
      fileModifiedAt: new Date().toISOString(),
      ...dto,
    };
    const assetData = dto?.assetData?.bytes || makeRandomImage();
    const filename = dto?.assetData?.filename || 'example.png';
    if (dto?.assetData?.bytes) {
      console.log(`Uploading ${filename}`);
    }
    const builder = request(app)
      .put(`/assets/${assetId}/original`)
      .attach('assetData', assetData, filename)
      .set('Authorization', `Bearer ${accessToken}`);
    for (const [key, value] of Object.entries(_dto)) {
      void builder.field(key, String(value));
    }
    const { body } = await builder;
    return body as AssetMediaResponseDto;
  },
  createImageFile: (path: string) => {
    if (!existsSync(dirname(path))) {
      mkdirSync(dirname(path), { recursive: true });
@@ -340,6 +376,9 @@ export const utils = {
  getAssetInfo: (accessToken: string, id: string) => getAssetInfo({ id }, { headers: asBearerAuth(accessToken) }),
  checkExistingAssets: (accessToken: string, checkExistingAssetsDto: CheckExistingAssetsDto) =>
    checkExistingAssets({ checkExistingAssetsDto }, { headers: asBearerAuth(accessToken) }),
  metadataSearch: async (accessToken: string, dto: MetadataSearchDto) => {
    return searchMetadata({ metadataSearchDto: dto }, { headers: asBearerAuth(accessToken) });
  },
@@ -0,0 +1,57 @@
 import { AssetMediaResponseDto, LoginResponseDto } from '@immich/sdk';
 import { Page, expect, test } from '@playwright/test';
 import { utils } from 'src/utils';
 function imageLocator(page: Page) {
  return page.getByAltText('Image taken on').locator('visible=true');
 }
 test.describe('Photo Viewer', () => {
  let admin: LoginResponseDto;
  let asset: AssetMediaResponseDto;
  test.beforeAll(async () => {
    utils.initSdk();
    await utils.resetDatabase();
    admin = await utils.adminSetup();
    asset = await utils.createAsset(admin.accessToken);
  });
  test.beforeEach(async ({ context, page }) => {
    // before each test, login as user
    await utils.setAuthCookies(context, admin.accessToken);
    await page.goto('/photos');
    await page.waitForLoadState('networkidle');
  });
  test('initially shows a loading spinner', async ({ page }) => {
    await page.route(`/api/assets/${asset.id}/thumbnail**`, async (route) => {
      // slow down the request for thumbnail, so spiner has chance to show up
      await new Promise((f) => setTimeout(f, 2000));
      await route.continue();
    });
    await page.goto(`/photos/${asset.id}`);
    await page.waitForLoadState('load');
    // this is the spinner
    await page.waitForSelector('svg[role=status]');
    await expect(page.getByRole('status')).toBeVisible();
  });
  test('loads high resolution photo when zoomed', async ({ page }) => {
    await page.goto(`/photos/${asset.id}`);
    await expect.poll(async () => await imageLocator(page).getAttribute('src')).toContain('thumbnail');
    const box = await imageLocator(page).boundingBox();
    expect(box).toBeTruthy;
    const { x, y, width, height } = box!;
    await page.mouse.move(x + width / 2, y + height / 2);
    await page.mouse.wheel(0, -1);
    await expect.poll(async () => await imageLocator(page).getAttribute('src')).toContain('original');
  });
  test('reloads photo when checksum changes', async ({ page }) => {
    await page.goto(`/photos/${asset.id}`);
    await expect.poll(async () => await imageLocator(page).getAttribute('src')).toContain('thumbnail');
    const initialSrc = await imageLocator(page).getAttribute('src');
    await utils.replaceAsset(admin.accessToken, asset.id);
    await expect.poll(async () => await imageLocator(page).getAttribute('src')).not.toBe(initialSrc);
  });
 });
@@ -12,8 +12,6 @@ from rich.logging import RichHandler
 from uvicorn import Server
 from uvicorn.workers import UvicornWorker
 from .schemas import ModelType
 class PreloadModelData(BaseModel):
    clip: str | None
@@ -21,7 +19,7 @@ class PreloadModelData(BaseModel):
 class Settings(BaseSettings):
-    cache_folder: str = "/cache"
+    cache_folder: Path = Path("/cache")
    model_ttl: int = 300
    model_ttl_poll_s: int = 10
    host: str = "0.0.0.0"
@@ -55,14 +53,6 @@ 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,
@@ -6,22 +6,34 @@ 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 import Depends, FastAPI, File, Form, HTTPException
 from fastapi.responses import ORJSONResponse
 from onnxruntime.capi.onnxruntime_pybind11_state import InvalidProtobuf, NoSuchFile
 from PIL.Image import Image
 from pydantic import ValidationError
 from starlette.formparsers import MultiPartParser
 from app.models import get_model_deps
 from app.models.base import InferenceModel
 from app.models.transforms import decode_pil
 from .config import PreloadModelData, log, settings
 from .models.cache import ModelCache
 from .schemas import (
    InferenceEntries,
    InferenceEntry,
    InferenceResponse,
    MessageResponse,
    ModelIdentity,
    ModelTask,
    ModelType,
    PipelineRequest,
    T,
    TextResponse,
 )
@@ -63,12 +75,21 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]:
        gc.collect()
-async def preload_models(preload_models: PreloadModelData) -> None:
+async def preload_models(preload: PreloadModelData) -> None:
-    log.info(f"Preloading models: {preload_models}")
+    log.info(f"Preloading models: {preload}")
-    if preload_models.clip is not None:
+    if preload.clip is not None:
-        await load(await model_cache.get(preload_models.clip, ModelType.CLIP))
+        model = await model_cache.get(preload.clip, ModelType.TEXTUAL, ModelTask.SEARCH)
-    if preload_models.facial_recognition is not None:
+        await load(model)
-        await load(await model_cache.get(preload_models.facial_recognition, ModelType.FACIAL_RECOGNITION))
+
        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)
 def update_state() -> Iterator[None]:
@@ -81,6 +102,27 @@ def update_state() -> Iterator[None]:
        active_requests -= 1
 def get_entries(entries: str = Form()) -> InferenceEntries:
    try:
        request: PipelineRequest = orjson.loads(entries)
        without_deps: list[InferenceEntry] = []
        with_deps: list[InferenceEntry] = []
        for task, types in request.items():
            for type, entry in types.items():
                parsed: InferenceEntry = {
                    "name": entry["modelName"],
                    "task": task,
                    "type": type,
                    "options": entry.get("options", {}),
                }
                dep = get_model_deps(parsed["name"], type, task)
                (with_deps if dep else without_deps).append(parsed)
        return without_deps, with_deps
    except (orjson.JSONDecodeError, ValidationError, KeyError, AttributeError) as e:
        log.error(f"Invalid request format: {e}")
        raise HTTPException(422, "Invalid request format.")
 app = FastAPI(lifespan=lifespan)
@@ -96,42 +138,63 @@ def ping() -> str:
@app.post("/predict", dependencies=[Depends(update_state)])
 async def predict(
-    model_name: str = Form(alias="modelName"),
+    entries: InferenceEntries = Depends(get_entries),
-    model_type: ModelType = Form(alias="modelType"),
+    image: bytes | None = File(default=None),
    options: str = Form(default="{}"),
    text: str | None = Form(default=None),
    image: UploadFile | None = None,
 ) -> Any:
    if image is not None:
-        inputs: str | bytes = await image.read()
+        inputs: Image | str = await run(lambda: decode_pil(image))
    elif text is not None:
        inputs = text
    else:
        raise HTTPException(400, "Either image or text must be provided")
-    try:
+    response = await run_inference(inputs, entries)
-        kwargs = orjson.loads(options)
+    return ORJSONResponse(response)
    except orjson.JSONDecodeError:
        raise HTTPException(400, f"Invalid options JSON: {options}")
    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], inputs: Any) -> Any:
+async def run_inference(payload: Image | str, entries: InferenceEntries) -> InferenceResponse:
    outputs: dict[ModelIdentity, Any] = {}
    response: InferenceResponse = {}
    async def _run_inference(entry: InferenceEntry) -> None:
        model = await model_cache.get(entry["name"], entry["type"], entry["task"], ttl=settings.model_ttl)
        inputs = [payload]
        for dep in model.depends:
            try:
                inputs.append(outputs[dep])
            except KeyError:
                message = f"Task {entry['task']} of type {entry['type']} depends on output of {dep}"
                raise HTTPException(400, message)
        model = await load(model)
        output = await run(model.predict, *inputs, **entry["options"])
        outputs[model.identity] = output
        response[entry["task"]] = output
    without_deps, with_deps = entries
    await asyncio.gather(*[_run_inference(entry) for entry in without_deps])
    if with_deps:
        await asyncio.gather(*[_run_inference(entry) for entry in with_deps])
    if isinstance(payload, Image):
        response["imageHeight"], response["imageWidth"] = payload.height, payload.width
    return response
 async def run(func: Callable[..., T], *args: Any, **kwargs: Any) -> T:
    if thread_pool is None:
-        return func(inputs)
+        return func(*args, **kwargs)
-    return await asyncio.get_running_loop().run_in_executor(thread_pool, func, inputs)
+    partial_func = partial(func, *args, **kwargs)
    return await asyncio.get_running_loop().run_in_executor(thread_pool, partial_func)
 async def load(model: InferenceModel) -> InferenceModel:
    if model.loaded:
        return model
-    def _load(model: InferenceModel) -> None:
+    def _load(model: InferenceModel) -> InferenceModel:
        with lock:
            model.load()
        return model
    try:
        await run(_load, model)
@@ -1,24 +1,40 @@
 from typing import Any
-from app.schemas import ModelType
+from app.models.base import InferenceModel
 from app.models.clip.textual import MClipTextualEncoder, OpenClipTextualEncoder
 from app.models.clip.visual import OpenClipVisualEncoder
 from app.schemas import ModelSource, ModelTask, ModelType
-from .base import InferenceModel
+from .constants import get_model_source
-from .clip import MCLIPEncoder, OpenCLIPEncoder
+from .facial_recognition.detection import FaceDetector
-from .constants import is_insightface, is_mclip, is_openclip
+from .facial_recognition.recognition import FaceRecognizer
 from .facial_recognition import FaceRecognizer
-def from_model_type(model_type: ModelType, model_name: str, **model_kwargs: Any) -> InferenceModel:
+def get_model_class(model_name: str, model_type: ModelType, model_task: ModelTask) -> type[InferenceModel]:
-    match model_type:
+    source = get_model_source(model_name)
-        case ModelType.CLIP:
+    match source, model_type, model_task:
-            if is_openclip(model_name):
+        case ModelSource.OPENCLIP | ModelSource.MCLIP, ModelType.VISUAL, ModelTask.SEARCH:
-                return OpenCLIPEncoder(model_name, **model_kwargs)
+            return OpenClipVisualEncoder
-            elif is_mclip(model_name):
+
-                return MCLIPEncoder(model_name, **model_kwargs)
+        case ModelSource.OPENCLIP, ModelType.TEXTUAL, ModelTask.SEARCH:
-        case ModelType.FACIAL_RECOGNITION:
+            return OpenClipTextualEncoder
-            if is_insightface(model_name):
+
-                return FaceRecognizer(model_name, **model_kwargs)
+        case ModelSource.MCLIP, ModelType.TEXTUAL, ModelTask.SEARCH:
            return MClipTextualEncoder
        case ModelSource.INSIGHTFACE, ModelType.DETECTION, ModelTask.FACIAL_RECOGNITION:
            return FaceDetector
        case ModelSource.INSIGHTFACE, ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION:
            return FaceRecognizer
        case _:
-            raise ValueError(f"Unknown model type {model_type}")
+            raise ValueError(f"Unknown model combination: {source}, {model_type}, {model_task}")
-    raise ValueError(f"Unknown {model_type} model {model_name}")
+
 def from_model_type(model_name: str, model_type: ModelType, model_task: ModelTask, **kwargs: Any) -> InferenceModel:
    return get_model_class(model_name, model_type, model_task)(model_name, **kwargs)
 def get_model_deps(model_name: str, model_type: ModelType, model_task: ModelTask) -> list[tuple[ModelType, ModelTask]]:
    return get_model_class(model_name, model_type, model_task).depends
@@ -3,7 +3,7 @@ from __future__ import annotations
 from abc import ABC, abstractmethod
 from pathlib import Path
 from shutil import rmtree
-from typing import Any
+from typing import Any, ClassVar
 import onnxruntime as ort
 from huggingface_hub import snapshot_download
@@ -11,13 +11,14 @@ from huggingface_hub import snapshot_download
 import ann.ann
 from app.models.constants import SUPPORTED_PROVIDERS
-from ..config import get_cache_dir, get_hf_model_name, log, settings
+from ..config import clean_name, log, settings
-from ..schemas import ModelRuntime, ModelType
+from ..schemas import ModelFormat, ModelIdentity, ModelSession, ModelTask, ModelType
 from .ann import AnnSession
 class InferenceModel(ABC):
-    _model_type: ModelType
+    depends: ClassVar[list[ModelIdentity]]
    identity: ClassVar[ModelIdentity]
    def __init__(
        self,
@@ -26,16 +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_runtime: ModelRuntime | None = None,
+        preferred_format: ModelFormat | None = None,
        **model_kwargs: Any,
    ) -> None:
        self.loaded = False
-        self.model_name = model_name
+        self.model_name = clean_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_runtime if preferred_runtime is not None else self.preferred_runtime_default
+        self.preferred_format = preferred_format if preferred_format is not None else self.preferred_format_default
    def download(self) -> None:
        if not self.cached:
@@ -47,35 +48,36 @@ class InferenceModel(ABC):
    def load(self) -> None:
        if self.loaded:
            return
        self.download()
        log.info(f"Loading {self.model_type.replace('-', ' ')} model '{self.model_name}' to memory")
-        self._load()
+        self.session = self._load()
        self.loaded = True
-    def predict(self, inputs: Any, **model_kwargs: Any) -> Any:
+    def predict(self, *inputs: Any, **model_kwargs: Any) -> Any:
        self.load()
        if model_kwargs:
            self.configure(**model_kwargs)
-        return self._predict(inputs)
+        return self._predict(*inputs, **model_kwargs)
    @abstractmethod
-    def _predict(self, inputs: Any) -> Any: ...
+    def _predict(self, *inputs: Any, **model_kwargs: Any) -> Any: ...
-    def configure(self, **model_kwargs: Any) -> None:
+    def configure(self, **kwargs: Any) -> None:
        pass
    def _download(self) -> None:
-        ignore_patterns = [] if self.preferred_runtime == ModelRuntime.ARMNN else ["*.armnn"]
+        ignore_patterns = [] if self.preferred_format == ModelFormat.ARMNN else ["*.armnn"]
        snapshot_download(
-            get_hf_model_name(self.model_name),
+            f"immich-app/{clean_name(self.model_name)}",
            cache_dir=self.cache_dir,
            local_dir=self.cache_dir,
            local_dir_use_symlinks=False,
            ignore_patterns=ignore_patterns,
        )
-    @abstractmethod
+    def _load(self) -> ModelSession:
-    def _load(self) -> None: ...
+        return self._make_session(self.model_path)
    def clear_cache(self) -> None:
        if not self.cache_dir.exists():
@@ -99,7 +101,7 @@ class InferenceModel(ABC):
            self.cache_dir.unlink()
        self.cache_dir.mkdir(parents=True, exist_ok=True)
-    def _make_session(self, model_path: Path) -> AnnSession | ort.InferenceSession:
+    def _make_session(self, model_path: Path) -> ModelSession:
        if not model_path.is_file():
            onnx_path = model_path.with_suffix(".onnx")
            if not onnx_path.is_file():
@@ -124,9 +126,21 @@ class InferenceModel(ABC):
                raise ValueError(f"Unsupported model file type: {model_path.suffix}")
        return session
    @property
    def model_dir(self) -> Path:
        return self.cache_dir / self.model_type.value
    @property
    def model_path(self) -> Path:
        return self.model_dir / f"model.{self.preferred_format}"
    @property
    def model_task(self) -> ModelTask:
        return self.identity[1]
    @property
    def model_type(self) -> ModelType:
-        return self._model_type
+        return self.identity[0]
    @property
    def cache_dir(self) -> Path:
@@ -138,11 +152,11 @@ class InferenceModel(ABC):
    @property
    def cache_dir_default(self) -> Path:
-        return get_cache_dir(self.model_name, self.model_type)
+        return settings.cache_folder / self.model_task.value / self.model_name
    @property
    def cached(self) -> bool:
-        return self.cache_dir.is_dir() and any(self.cache_dir.iterdir())
+        return self.model_path.is_file()
    @property
    def providers(self) -> list[str]:
@@ -226,14 +240,14 @@ class InferenceModel(ABC):
        return sess_options
    @property
-    def preferred_runtime(self) -> ModelRuntime:
+    def preferred_format(self) -> ModelFormat:
-        return self._preferred_runtime
+        return self._preferred_format
-    @preferred_runtime.setter
+    @preferred_format.setter
-    def preferred_runtime(self, preferred_runtime: ModelRuntime) -> None:
+    def preferred_format(self, preferred_format: ModelFormat) -> None:
-        log.debug(f"Setting preferred runtime to {preferred_runtime}")
+        log.debug(f"Setting preferred format to {preferred_format}")
-        self._preferred_runtime = preferred_runtime
+        self._preferred_format = preferred_format
    @property
-    def preferred_runtime_default(self) -> ModelRuntime:
+    def preferred_format_default(self) -> ModelFormat:
-        return ModelRuntime.ARMNN if ann.ann.is_available and settings.ann else ModelRuntime.ONNX
+        return ModelFormat.ARMNN if ann.ann.is_available and settings.ann else ModelFormat.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.base import InferenceModel
-from ..schemas import ModelType, has_profiling
+from ..schemas import ModelTask, ModelType, has_profiling
 from .base import InferenceModel
 class ModelCache:
@@ -31,28 +31,21 @@ class ModelCache:
        if profiling:
            plugins.append(TimingPlugin())
-        self.revalidate_enable = revalidate
+        self.should_revalidate = revalidate
        self.cache = SimpleMemoryCache(timeout=timeout, plugins=plugins, namespace=None)
-    async def get(self, model_name: str, model_type: ModelType, **model_kwargs: Any) -> InferenceModel:
+    async def get(
-        """
+        self, model_name: str, model_type: ModelType, model_task: ModelTask, **model_kwargs: Any
-        Args:
+    ) -> InferenceModel:
-            model_name: Name of model in the model hub used for the task.
+        key = f"{model_name}{model_type}{model_task}"
            model_type: Model type or task, which determines which model zoo is used.
        Returns:
            model: The requested model.
        """
        key = f"{model_name}{model_type.value}{model_kwargs.get('mode', '')}"
        async with OptimisticLock(self.cache, key) as lock:
            model: InferenceModel | None = await self.cache.get(key)
            if model is None:
-                model = from_model_type(model_type, model_name, **model_kwargs)
+                model = from_model_type(model_name, model_type, model_task, **model_kwargs)
                await lock.cas(model, ttl=model_kwargs.get("ttl", None))
-            elif self.revalidate_enable:
+            elif self.should_revalidate:
                await self.revalidate(key, model_kwargs.get("ttl", None))
        return model
@@ -1,189 +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, 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),
        }
@@ -0,0 +1,98 @@
 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.models.base import InferenceModel
 from app.schemas import ModelSession, ModelTask, ModelType
 class BaseCLIPTextualEncoder(InferenceModel):
    depends = []
    identity = (ModelType.TEXTUAL, ModelTask.SEARCH)
    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_cfg_path(self) -> Path:
        return self.cache_dir / "config.json"
    @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"
    @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),
        }
@@ -0,0 +1,69 @@
 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 PIL import Image
 from app.config import log
 from app.models.base import InferenceModel
 from app.models.transforms import crop_pil, decode_pil, get_pil_resampling, normalize, resize_pil, to_numpy
 from app.schemas import ModelSession, ModelTask, ModelType
 class BaseCLIPVisualEncoder(InferenceModel):
    depends = []
    identity = (ModelType.VISUAL, ModelTask.SEARCH)
    def _predict(self, inputs: Image.Image | bytes, **kwargs: Any) -> NDArray[np.float32]:
        image = decode_pil(inputs)
        res: NDArray[np.float32] = self.session.run(None, self.transform(image))[0][0]
        return res
    @abstractmethod
    def transform(self, image: Image.Image) -> dict[str, NDArray[np.float32]]:
        pass
    @property
    def model_cfg_path(self) -> Path:
        return self.cache_dir / "config.json"
    @property
    def preprocess_cfg_path(self) -> Path:
        return self.model_dir / "preprocess_cfg.json"
    @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)}
@@ -1,4 +1,5 @@
 from app.config import clean_name
 from app.schemas import ModelSource
 _OPENCLIP_MODELS = {
    "RN50__openai",
@@ -54,13 +55,16 @@ _INSIGHTFACE_MODELS = {
 SUPPORTED_PROVIDERS = ["CUDAExecutionProvider", "OpenVINOExecutionProvider", "CPUExecutionProvider"]
-def is_openclip(model_name: str) -> bool:
+def get_model_source(model_name: str) -> ModelSource | None:
-    return clean_name(model_name) in _OPENCLIP_MODELS
+    cleaned_name = clean_name(model_name)
    if cleaned_name in _INSIGHTFACE_MODELS:
        return ModelSource.INSIGHTFACE
-def is_mclip(model_name: str) -> bool:
+    if cleaned_name in _MCLIP_MODELS:
-    return clean_name(model_name) in _MCLIP_MODELS
+        return ModelSource.MCLIP
    if cleaned_name in _OPENCLIP_MODELS:
        return ModelSource.OPENCLIP
-def is_insightface(model_name: str) -> bool:
+    return None
    return clean_name(model_name) in _INSIGHTFACE_MODELS
@@ -1,90 +0,0 @@
 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)
@@ -0,0 +1,48 @@
 from pathlib import Path
 from typing import Any
 import numpy as np
 from insightface.model_zoo import RetinaFace
 from numpy.typing import NDArray
 from app.models.base import InferenceModel
 from app.models.transforms import decode_cv2
 from app.schemas import FaceDetectionOutput, ModelSession, ModelTask, ModelType
 class FaceDetector(InferenceModel):
    depends = []
    identity = (ModelType.DETECTION, ModelTask.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__(model_name, cache_dir, **model_kwargs)
    def _load(self) -> ModelSession:
        session = self._make_session(self.model_path)
        self.model = RetinaFace(session=session)
        self.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) -> FaceDetectionOutput:
        inputs = decode_cv2(inputs)
        bboxes, landmarks = self._detect(inputs)
        return {
            "boxes": bboxes[:, :4].round(),
            "scores": bboxes[:, 4],
            "landmarks": landmarks,
        }
    def _detect(self, inputs: NDArray[np.uint8] | bytes) -> tuple[NDArray[np.float32], NDArray[np.float32]]:
        return self.model.detect(inputs)  # type: ignore
    def configure(self, **kwargs: Any) -> None:
        self.model.det_thresh = kwargs.pop("minScore", self.model.det_thresh)
@@ -0,0 +1,77 @@
 from pathlib import Path
 from typing import Any
 import numpy as np
 import onnx
 import onnxruntime as ort
 from insightface.model_zoo import ArcFaceONNX
 from insightface.utils.face_align import norm_crop
 from numpy.typing import NDArray
 from onnx.tools.update_model_dims import update_inputs_outputs_dims
 from PIL import Image
 from app.config import clean_name, log
 from app.models.base import InferenceModel
 from app.models.transforms import decode_cv2
 from app.schemas import FaceDetectionOutput, FacialRecognitionOutput, ModelSession, ModelTask, ModelType
 class FaceRecognizer(InferenceModel):
    depends = [(ModelType.DETECTION, ModelTask.FACIAL_RECOGNITION)]
    identity = (ModelType.RECOGNITION, ModelTask.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) -> ModelSession:
        session = self._make_session(self.model_path)
        if not self._has_batch_dim(session):
            self._add_batch_dim(self.model_path)
            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, inputs: NDArray[np.uint8] | bytes | Image.Image, faces: FaceDetectionOutput, **kwargs: Any
    ) -> FacialRecognitionOutput:
        if faces["boxes"].shape[0] == 0:
            return []
        inputs = decode_cv2(inputs)
        embeddings: NDArray[np.float32] = self.model.get_feat(self._crop(inputs, faces))
        return self.postprocess(faces, embeddings)
    def postprocess(self, faces: FaceDetectionOutput, embeddings: NDArray[np.float32]) -> FacialRecognitionOutput:
        return [
            {
                "boundingBox": {"x1": x1, "y1": y1, "x2": x2, "y2": y2},
                "embedding": embedding,
                "score": score,
            }
            for (x1, y1, x2, y2), embedding, score in zip(faces["boxes"], embeddings, faces["scores"])
        ]
    def _crop(self, image: NDArray[np.uint8], faces: FaceDetectionOutput) -> list[NDArray[np.uint8]]:
        return [norm_crop(image, landmark) for landmark in faces["landmarks"]]
    def _has_batch_dim(self, session: ort.InferenceSession) -> bool:
        return not isinstance(session, ort.InferenceSession) or session.get_inputs()[0].shape[0] == "batch"
    def _add_batch_dim(self, model_path: Path) -> None:
        log.debug(f"Adding batch dimension to model {model_path}")
        proto = onnx.load(model_path)
        static_input_dims = [shape.dim_value for shape in proto.graph.input[0].type.tensor_type.shape.dim[1:]]
        static_output_dims = [shape.dim_value for shape in proto.graph.output[0].type.tensor_type.shape.dim[1:]]
        input_dims = {proto.graph.input[0].name: ["batch"] + static_input_dims}
        output_dims = {proto.graph.output[0].name: ["batch"] + static_output_dims}
        updated_proto = update_inputs_outputs_dims(proto, input_dims, output_dims)
        onnx.save(updated_proto, model_path)
@@ -1,3 +1,7 @@
 from io import BytesIO
 from typing import IO
 import cv2
 import numpy as np
 from numpy.typing import NDArray
 from PIL import Image
@@ -5,7 +9,7 @@ from PIL import Image
 _PIL_RESAMPLING_METHODS = {resampling.name.lower(): resampling for resampling in Image.Resampling}
-def resize(img: Image.Image, size: int) -> Image.Image:
+def resize_pil(img: Image.Image, size: int) -> Image.Image:
    if img.width < img.height:
        return img.resize((size, int((img.height / img.width) * size)), resample=Image.Resampling.BICUBIC)
    else:
@@ -13,7 +17,7 @@ def resize(img: Image.Image, size: int) -> Image.Image:
 # https://stackoverflow.com/a/60883103
-def crop(img: Image.Image, size: int) -> Image.Image:
+def crop_pil(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
@@ -23,14 +27,36 @@ def crop(img: Image.Image, size: int) -> Image.Image:
 def to_numpy(img: Image.Image) -> NDArray[np.float32]:
-    return np.asarray(img.convert("RGB")).astype(np.float32) / 255.0
+    return np.asarray(img if img.mode == "RGB" else img.convert("RGB"), dtype=np.float32) / 255.0
 def normalize(
    img: NDArray[np.float32], mean: float | NDArray[np.float32], std: float | NDArray[np.float32]
 ) -> NDArray[np.float32]:
-    return (img - mean) / std
+    return np.divide(img - mean, std, dtype=np.float32)
 def get_pil_resampling(resample: str) -> Image.Resampling:
    return _PIL_RESAMPLING_METHODS[resample.lower()]
 def pil_to_cv2(image: Image.Image) -> NDArray[np.uint8]:
    return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)  # type: ignore
 def decode_pil(image_bytes: bytes | IO[bytes] | Image.Image) -> Image.Image:
    if isinstance(image_bytes, Image.Image):
        return image_bytes
    image = Image.open(BytesIO(image_bytes) if isinstance(image_bytes, bytes) else image_bytes)
    image.load()  # type: ignore
    if not image.mode == "RGB":
        image = image.convert("RGB")
    return image
 def decode_cv2(image_bytes: NDArray[np.uint8] | bytes | Image.Image) -> NDArray[np.uint8]:
    if isinstance(image_bytes, bytes):
        image_bytes = decode_pil(image_bytes)  # pillow is much faster than cv2
    if isinstance(image_bytes, Image.Image):
        return pil_to_cv2(image_bytes)
    return image_bytes
@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Any, Protocol, TypedDict, TypeGuard
+from typing import Any, Literal, Protocol, TypedDict, TypeGuard, TypeVar
 import numpy as np
 import numpy.typing as npt
@@ -28,31 +28,87 @@ class BoundingBox(TypedDict):
    y2: int
-class ModelType(StrEnum):
+class ModelTask(StrEnum):
    CLIP = "clip"
    FACIAL_RECOGNITION = "facial-recognition"
    SEARCH = "clip"
-class ModelRuntime(StrEnum):
+class ModelType(StrEnum):
-    ONNX = "onnx"
+    DETECTION = "detection"
    RECOGNITION = "recognition"
    TEXTUAL = "textual"
    VISUAL = "visual"
 class ModelFormat(StrEnum):
    ARMNN = "armnn"
    ONNX = "onnx"
 class ModelSource(StrEnum):
    INSIGHTFACE = "insightface"
    MCLIP = "mclip"
    OPENCLIP = "openclip"
 ModelIdentity = tuple[ModelType, ModelTask]
 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 HasProfiling(Protocol):
    profiling: dict[str, float]
-class Face(TypedDict):
+class FaceDetectionOutput(TypedDict):
    boxes: npt.NDArray[np.float32]
    scores: npt.NDArray[np.float32]
    landmarks: npt.NDArray[np.float32]
 class DetectedFace(TypedDict):
    boundingBox: BoundingBox
    embedding: npt.NDArray[np.float32]
    imageWidth: int
    imageHeight: int
    score: float
 FacialRecognitionOutput = list[DetectedFace]
 class PipelineEntry(TypedDict):
    modelName: str
    options: dict[str, Any]
 PipelineRequest = dict[ModelTask, dict[ModelType, PipelineEntry]]
 class InferenceEntry(TypedDict):
    name: str
    task: ModelTask
    type: ModelType
    options: dict[str, Any]
 InferenceEntries = tuple[list[InferenceEntry], list[InferenceEntry]]
 InferenceResponse = dict[ModelTask | Literal["imageHeight"] | Literal["imageWidth"], Any]
 def has_profiling(obj: Any) -> TypeGuard[HasProfiling]:
    return hasattr(obj, "profiling") and isinstance(obj.profiling, dict)
 def is_ndarray(obj: Any, dtype: "type[np._DTypeScalar_co]") -> "TypeGuard[npt.NDArray[np._DTypeScalar_co]]":
    return isinstance(obj, np.ndarray) and obj.dtype == dtype
 T = TypeVar("T")
@@ -17,13 +17,15 @@ 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.detection import FaceDetector
 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 .models.clip import MCLIPEncoder, OpenCLIPEncoder
+from .schemas import ModelFormat, ModelTask, ModelType
 from .models.facial_recognition import FaceRecognizer
 from .schemas import ModelRuntime, ModelType
 class TestBase:
@@ -35,13 +37,13 @@ class TestBase:
    @pytest.mark.providers(CPU_EP)
    def test_sets_cpu_provider(self, providers: list[str]) -> None:
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("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 = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
        assert encoder.providers == self.CUDA_EP
@@ -50,7 +52,7 @@ class TestBase:
        mocked = mocker.patch("app.models.base.ort.capi._pybind_state")
        mocked.get_available_openvino_device_ids.return_value = ["GPU.0", "CPU"]
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
        assert encoder.providers == self.OV_EP
@@ -59,25 +61,25 @@ class TestBase:
        mocked = mocker.patch("app.models.base.ort.capi._pybind_state")
        mocked.get_available_openvino_device_ids.return_value = ["CPU"]
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("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 = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("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 = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
        assert encoder.providers == self.CUDA_EP
    def test_sets_provider_kwarg(self) -> None:
        providers = ["CUDAExecutionProvider"]
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=providers)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", providers=providers)
        assert encoder.providers == providers
@@ -85,7 +87,9 @@ class TestBase:
        mocked = mocker.patch("app.models.base.ort.capi._pybind_state")
        mocked.get_available_openvino_device_ids.return_value = ["GPU.0", "CPU"]
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"])
+        encoder = OpenClipTextualEncoder(
            "ViT-B-32__openai", providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"]
        )
        assert encoder.provider_options == [
            {"device_type": "GPU_FP32", "cache_dir": (encoder.cache_dir / "openvino").as_posix()},
@@ -93,7 +97,7 @@ class TestBase:
        ]
    def test_sets_provider_options_kwarg(self) -> None:
-        encoder = OpenCLIPEncoder(
+        encoder = OpenClipTextualEncoder(
            "ViT-B-32__openai",
            providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"],
            provider_options=[],
@@ -102,7 +106,7 @@ class TestBase:
        assert encoder.provider_options == []
    def test_sets_default_sess_options(self) -> None:
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
        assert encoder.sess_options.execution_mode == ort.ExecutionMode.ORT_SEQUENTIAL
        assert encoder.sess_options.inter_op_num_threads == 1
@@ -110,7 +114,9 @@ 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 = OpenCLIPEncoder("ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"])
+        encoder = OpenClipTextualEncoder(
            "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
@@ -120,14 +126,16 @@ class TestBase:
        mock_settings.model_inter_op_threads = 2
        mock_settings.model_intra_op_threads = 4
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", providers=["CUDAExecutionProvider", "CPUExecutionProvider"])
+        encoder = OpenClipTextualEncoder(
            "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 = OpenCLIPEncoder(
+        encoder = OpenClipTextualEncoder(
            "ViT-B-32__openai",
            providers=["OpenVINOExecutionProvider", "CPUExecutionProvider"],
            provider_options=[],
@@ -137,43 +145,43 @@ class TestBase:
        assert sess_options is encoder.sess_options
    def test_sets_default_cache_dir(self) -> None:
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("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 = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=cache_dir)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=cache_dir)
        assert encoder.cache_dir == cache_dir
-    def test_sets_default_preferred_runtime(self, mocker: MockerFixture) -> None:
+    def test_sets_default_preferred_format(self, mocker: MockerFixture) -> None:
        mocker.patch.object(settings, "ann", True)
        mocker.patch("ann.ann.is_available", False)
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
-        assert encoder.preferred_runtime == ModelRuntime.ONNX
+        assert encoder.preferred_format == ModelFormat.ONNX
-    def test_sets_default_preferred_runtime_to_armnn_if_available(self, mocker: MockerFixture) -> None:
+    def test_sets_default_preferred_format_to_armnn_if_available(self, mocker: MockerFixture) -> None:
        mocker.patch.object(settings, "ann", True)
        mocker.patch("ann.ann.is_available", True)
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
-        assert encoder.preferred_runtime == ModelRuntime.ARMNN
+        assert encoder.preferred_format == ModelFormat.ARMNN
-    def test_sets_preferred_runtime_kwarg(self, mocker: MockerFixture) -> None:
+    def test_sets_preferred_format_kwarg(self, mocker: MockerFixture) -> None:
        mocker.patch.object(settings, "ann", False)
        mocker.patch("ann.ann.is_available", False)
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", preferred_runtime=ModelRuntime.ARMNN)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", preferred_format=ModelFormat.ARMNN)
-        assert encoder.preferred_runtime == ModelRuntime.ARMNN
+        assert encoder.preferred_format == ModelFormat.ARMNN
    def test_casts_cache_dir_string_to_path(self) -> None:
        cache_dir = "/test_cache"
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=cache_dir)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=cache_dir)
        assert encoder.cache_dir == Path(cache_dir)
@@ -186,7 +194,7 @@ class TestBase:
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
        info = mocker.spy(log, "info")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        encoder.clear_cache()
        mock_rmtree.assert_called_once_with(encoder.cache_dir)
@@ -201,7 +209,7 @@ class TestBase:
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
        warning = mocker.spy(log, "warning")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        encoder.clear_cache()
        mock_rmtree.assert_not_called()
@@ -215,7 +223,7 @@ class TestBase:
        mock_cache_dir.is_dir.return_value = True
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        with pytest.raises(RuntimeError):
            encoder.clear_cache()
@@ -230,7 +238,7 @@ class TestBase:
        mocker.patch("app.models.base.Path", return_value=mock_cache_dir)
        warning = mocker.spy(log, "warning")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir=mock_cache_dir)
        encoder.clear_cache()
        mock_rmtree.assert_not_called()
@@ -245,7 +253,7 @@ class TestBase:
        mock_model_path.with_suffix.return_value = mock_model_path
        mock_ann = mocker.patch("app.models.base.AnnSession")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
        encoder._make_session(mock_model_path)
        mock_ann.assert_called_once()
@@ -263,7 +271,7 @@ class TestBase:
        mock_ann = mocker.patch("app.models.base.AnnSession")
        mock_ort = mocker.patch("app.models.base.ort.InferenceSession")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
        encoder._make_session(mock_armnn_path)
        mock_ort.assert_called_once()
@@ -277,7 +285,7 @@ class TestBase:
        mock_ann = mocker.patch("app.models.base.AnnSession")
        mock_ort = mocker.patch("app.models.base.ort.InferenceSession")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai")
        with pytest.raises(ValueError):
            encoder._make_session(mock_model_path)
@@ -287,7 +295,7 @@ class TestBase:
    def test_download(self, mocker: MockerFixture) -> None:
        mock_snapshot_download = mocker.patch("app.models.base.snapshot_download")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="/path/to/cache")
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir="/path/to/cache")
        encoder.download()
        mock_snapshot_download.assert_called_once_with(
@@ -298,10 +306,10 @@ class TestBase:
            ignore_patterns=["*.armnn"],
        )
-    def test_download_downloads_armnn_if_preferred_runtime(self, mocker: MockerFixture) -> None:
+    def test_download_downloads_armnn_if_preferred_format(self, mocker: MockerFixture) -> None:
        mock_snapshot_download = mocker.patch("app.models.base.snapshot_download")
-        encoder = OpenCLIPEncoder("ViT-B-32__openai", preferred_runtime=ModelRuntime.ARMNN)
+        encoder = OpenClipTextualEncoder("ViT-B-32__openai", preferred_format=ModelFormat.ARMNN)
        encoder.download()
        mock_snapshot_download.assert_called_once_with(
@@ -323,21 +331,17 @@ 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(OpenCLIPEncoder, "download")
+        mocker.patch.object(OpenClipVisualEncoder, "download")
-        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(OpenClipVisualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenClipVisualEncoder, "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 = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="vision")
+        clip_encoder = OpenClipVisualEncoder("ViT-B-32__openai", cache_dir="test_cache")
        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
@@ -347,22 +351,19 @@ 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(OpenCLIPEncoder, "download")
+        mocker.patch.object(OpenClipTextualEncoder, "download")
-        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(OpenClipTextualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_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)
+        mocker.patch("app.models.clip.textual.Tokenizer.from_file", autospec=True)
-        clip_encoder = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
+        clip_encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir="test_cache")
        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
@@ -372,19 +373,18 @@ 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(OpenCLIPEncoder, "download")
+        mocker.patch.object(OpenClipTextualEncoder, "download")
-        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(OpenClipTextualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(OpenClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
-        mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
+        mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
-        mock_tokenizer = mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True).return_value
+        mock_tokenizer = mocker.patch("app.models.clip.textual.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 = OpenCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
+        clip_encoder = OpenClipTextualEncoder("ViT-B-32__openai", cache_dir="test_cache")
-        clip_encoder._load_tokenizer()
+        clip_encoder._load()
        tokens = clip_encoder.tokenize("test search query")
        assert "text" in tokens
@@ -397,20 +397,19 @@ 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(OpenCLIPEncoder, "download")
+        mocker.patch.object(MClipTextualEncoder, "download")
-        mocker.patch.object(OpenCLIPEncoder, "model_cfg", clip_model_cfg)
+        mocker.patch.object(MClipTextualEncoder, "model_cfg", clip_model_cfg)
-        mocker.patch.object(OpenCLIPEncoder, "preprocess_cfg", clip_preprocess_cfg)
+        mocker.patch.object(MClipTextualEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
-        mocker.patch.object(OpenCLIPEncoder, "tokenizer_cfg", clip_tokenizer_cfg)
+        mocker.patch.object(InferenceModel, "_make_session", autospec=True).return_value
-        mock_tokenizer = mocker.patch("app.models.clip.Tokenizer.from_file", autospec=True).return_value
+        mock_tokenizer = mocker.patch("app.models.clip.textual.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 = MCLIPEncoder("ViT-B-32__openai", cache_dir="test_cache", mode="text")
+        clip_encoder = MClipTextualEncoder("ViT-B-32__openai", cache_dir="test_cache")
-        clip_encoder._load_tokenizer()
+        clip_encoder._load()
        tokens = clip_encoder.tokenize("test search query")
        assert "input_ids" in tokens
@@ -430,59 +429,90 @@ class TestFaceRecognition:
        assert face_recognizer.min_score == 0.5
-    def test_basic(self, cv_image: cv2.Mat, mocker: MockerFixture) -> None:
+    def test_detection(self, cv_image: cv2.Mat, mocker: MockerFixture) -> None:
-        mocker.patch.object(FaceRecognizer, "load")
+        mocker.patch.object(FaceDetector, "load")
-        face_recognizer = FaceRecognizer("buffalo_s", min_score=0.0, cache_dir="test_cache")
+        face_detector = FaceDetector("buffalo_s", min_score=0.0, cache_dir="test_cache")
        det_model = mock.Mock()
        num_faces = 2
        bbox = np.random.rand(num_faces, 4).astype(np.float32)
-        score = np.array([[0.67]] * num_faces).astype(np.float32)
+        scores = 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)
+        det_model.detect.return_value = (np.concatenate([bbox, scores], axis=-1), kpss)
-        face_recognizer.det_model = det_model
+        face_detector.model = det_model
        faces = face_detector.predict(cv_image)
        assert isinstance(faces, dict)
        assert isinstance(faces.get("boxes", None), np.ndarray)
        assert isinstance(faces.get("landmarks", None), np.ndarray)
        assert isinstance(faces.get("scores", None), np.ndarray)
        assert np.equal(faces["boxes"], bbox.round()).all()
        assert np.equal(faces["landmarks"], kpss).all()
        assert np.equal(faces["scores"], scores).all()
        det_model.detect.assert_called_once()
    def test_recognition(self, cv_image: cv2.Mat, mocker: MockerFixture) -> None:
        mocker.patch.object(FaceRecognizer, "load")
        face_recognizer = FaceRecognizer("buffalo_s", min_score=0.0, cache_dir="test_cache")
        num_faces = 2
        bbox = np.random.rand(num_faces, 4).astype(np.float32)
        scores = np.array([0.67] * num_faces).astype(np.float32)
        kpss = np.random.rand(num_faces, 5, 2).astype(np.float32)
        faces = {"boxes": bbox, "landmarks": kpss, "scores": scores}
        rec_model = mock.Mock()
        embedding = np.random.rand(num_faces, 512).astype(np.float32)
        rec_model.get_feat.return_value = embedding
-        face_recognizer.rec_model = rec_model
+        face_recognizer.model = rec_model
-        faces = face_recognizer.predict(cv_image)
+        faces = face_recognizer.predict(cv_image, faces)
        assert isinstance(faces, list)
        assert len(faces) == num_faces
        for face in faces:
-            assert face["imageHeight"] == 800
+            assert isinstance(face.get("boundingBox"), dict)
-            assert face["imageWidth"] == 600
+            assert set(face["boundingBox"]) == {"x1", "y1", "x2", "y2"}
-            assert isinstance(face["embedding"], np.ndarray)
+            assert all(isinstance(val, np.float32) for val in face["boundingBox"].values())
            assert isinstance(face.get("embedding"), np.ndarray)
            assert face["embedding"].shape[0] == 512
-            assert face["embedding"].dtype == np.float32
+            assert isinstance(face.get("score", None), np.float32)
-        det_model.detect.assert_called_once()
+        rec_model.get_feat.assert_called_once()
-        assert rec_model.get_feat.call_count == num_faces
+        call_args = rec_model.get_feat.call_args_list[0].args
        assert len(call_args) == 1
        assert isinstance(call_args[0], list)
        assert isinstance(call_args[0][0], np.ndarray)
        assert call_args[0][0].shape == (112, 112, 3)
@pytest.mark.asyncio
 class TestCache:
    async def test_caches(self, mock_get_model: mock.Mock) -> None:
        model_cache = ModelCache()
-        await model_cache.get("test_model_name", ModelType.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.RECOGNITION, ModelTask.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.FACIAL_RECOGNITION, cache_dir="test_cache")
+        await model_cache.get(
-        mock_get_model.assert_called_once_with(ModelType.FACIAL_RECOGNITION, "test_model_name", cache_dir="test_cache")
+            "test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, cache_dir="test_cache"
        )
        mock_get_model.assert_called_once_with(
            "test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, 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.CLIP)
+        await model_cache.get("test_model_name", ModelType.VISUAL, ModelTask.SEARCH)
-        await model_cache.get("test_text_model_name", ModelType.CLIP)
+        await model_cache.get("test_model_name", ModelType.TEXTUAL, ModelTask.SEARCH)
        mock_get_model.assert_has_calls(
            [
-                mock.call(ModelType.CLIP, "test_image_model_name"),
+                mock.call("test_model_name", ModelType.VISUAL, ModelTask.SEARCH),
-                mock.call(ModelType.CLIP, "test_text_model_name"),
+                mock.call("test_model_name", ModelType.TEXTUAL, ModelTask.SEARCH),
            ]
        )
        assert len(model_cache.cache._cache) == 2
@@ -490,19 +520,19 @@ 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.FACIAL_RECOGNITION, ttl=100)
+        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.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.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.RECOGNITION, ModelTask.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.FACIAL_RECOGNITION, ttl=100)
+        await model_cache.get("test_model_name", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION, ttl=100)
        profiling = await model_cache.get_profiling()
        assert isinstance(profiling, dict)
        assert profiling == model_cache.cache.profiling
@@ -510,9 +540,9 @@ class TestCache:
    async def test_loads_mclip(self) -> None:
        model_cache = ModelCache()
-        model = await model_cache.get("XLM-Roberta-Large-Vit-B-32", ModelType.CLIP, mode="text")
+        model = await model_cache.get("XLM-Roberta-Large-Vit-B-32", ModelType.TEXTUAL, ModelTask.SEARCH)
-        assert isinstance(model, MCLIPEncoder)
+        assert isinstance(model, MClipTextualEncoder)
        assert model.model_name == "XLM-Roberta-Large-Vit-B-32"
    async def test_raises_exception_if_invalid_model_type(self) -> None:
@@ -520,15 +550,55 @@ class TestCache:
        model_cache = ModelCache()
        with pytest.raises(ValueError):
-            await model_cache.get("XLM-Roberta-Large-Vit-B-32", invalid, mode="text")
+            await model_cache.get("XLM-Roberta-Large-Vit-B-32", ModelType.TEXTUAL, invalid)
    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.CLIP, mode="text")
+            await model_cache.get("test_model_name", ModelType.TEXTUAL, ModelTask.SEARCH)
-    async def test_preloads_models(self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock) -> None:
+    async def test_preloads_clip_models(self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock) -> None:
        os.environ["MACHINE_LEARNING_PRELOAD__CLIP"] = "ViT-B-32__openai"
        settings = Settings()
        assert settings.preload is not None
        assert settings.preload.clip == "ViT-B-32__openai"
        model_cache = ModelCache()
        monkeypatch.setattr("app.main.model_cache", model_cache)
        await preload_models(settings.preload)
        mock_get_model.assert_has_calls(
            [
                mock.call("ViT-B-32__openai", ModelType.TEXTUAL, ModelTask.SEARCH),
                mock.call("ViT-B-32__openai", ModelType.VISUAL, ModelTask.SEARCH),
            ],
            any_order=True,
        )
    async def test_preloads_facial_recognition_models(
        self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock
    ) -> None:
        os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION"] = "buffalo_s"
        settings = Settings()
        assert settings.preload is not None
        assert settings.preload.facial_recognition == "buffalo_s"
        model_cache = ModelCache()
        monkeypatch.setattr("app.main.model_cache", model_cache)
        await preload_models(settings.preload)
        mock_get_model.assert_has_calls(
            [
                mock.call("buffalo_s", ModelType.DETECTION, ModelTask.FACIAL_RECOGNITION),
                mock.call("buffalo_s", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION),
            ],
            any_order=True,
        )
    async def test_preloads_all_models(self, monkeypatch: MonkeyPatch, mock_get_model: mock.Mock) -> None:
        os.environ["MACHINE_LEARNING_PRELOAD__CLIP"] = "ViT-B-32__openai"
        os.environ["MACHINE_LEARNING_PRELOAD__FACIAL_RECOGNITION"] = "buffalo_s"
@@ -541,11 +611,15 @@ class TestCache:
        monkeypatch.setattr("app.main.model_cache", model_cache)
        await preload_models(settings.preload)
-        assert len(model_cache.cache._cache) == 2
+        mock_get_model.assert_has_calls(
-        assert mock_get_model.call_count == 2
+            [
-        await model_cache.get("ViT-B-32__openai", ModelType.CLIP, ttl=100)
+                mock.call("ViT-B-32__openai", ModelType.TEXTUAL, ModelTask.SEARCH),
-        await model_cache.get("buffalo_s", ModelType.FACIAL_RECOGNITION, ttl=100)
+                mock.call("ViT-B-32__openai", ModelType.VISUAL, ModelTask.SEARCH),
-        assert mock_get_model.call_count == 2
+                mock.call("buffalo_s", ModelType.DETECTION, ModelTask.FACIAL_RECOGNITION),
                mock.call("buffalo_s", ModelType.RECOGNITION, ModelTask.FACIAL_RECOGNITION),
            ],
            any_order=True,
        )
@pytest.mark.asyncio
@@ -572,7 +646,8 @@ 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.CLIP
+        mock_model.model_type = ModelType.VISUAL
        mock_model.model_task = ModelTask.SEARCH
        mock_model.load.side_effect = [OSError, None]
        mock_model.loaded = False
@@ -597,13 +672,15 @@ class TestEndpoints:
        response = deployed_app.post(
            "http://localhost:3003/predict",
-            data={"modelName": "ViT-B-32__openai", "modelType": "clip", "options": json.dumps({"mode": "vision"})},
+            data={"entries": json.dumps({"clip": {"visual": {"modelName": "ViT-B-32__openai"}}})},
            files={"image": byte_image.getvalue()},
        )
        actual = response.json()
        assert response.status_code == 200
-        assert np.allclose(expected, actual)
+        assert isinstance(actual, dict)
        assert isinstance(actual.get("clip", None), list)
        assert np.allclose(expected, actual["clip"])
    def test_clip_text_endpoint(self, responses: dict[str, Any], deployed_app: TestClient) -> None:
        expected = responses["clip"]["text"]
@@ -611,38 +688,49 @@ class TestEndpoints:
        response = deployed_app.post(
            "http://localhost:3003/predict",
            data={
-                "modelName": "ViT-B-32__openai",
+                "entries": json.dumps(
-                "modelType": "clip",
+                    {
                        "clip": {"textual": {"modelName": "ViT-B-32__openai"}},
                    },
                ),
                "text": "test search query",
                "options": json.dumps({"mode": "text"}),
            },
        )
        actual = response.json()
        assert response.status_code == 200
-        assert np.allclose(expected, actual)
+        assert isinstance(actual, dict)
        assert isinstance(actual.get("clip", None), list)
        assert np.allclose(expected, actual["clip"])
    def test_face_endpoint(self, pil_image: Image.Image, responses: dict[str, Any], deployed_app: TestClient) -> None:
        byte_image = BytesIO()
        pil_image.save(byte_image, format="jpeg")
        expected = responses["facial-recognition"]
        response = deployed_app.post(
            "http://localhost:3003/predict",
            data={
-                "modelName": "buffalo_l",
+                "entries": json.dumps(
-                "modelType": "facial-recognition",
+                    {
-                "options": json.dumps({"minScore": 0.034}),
+                        "facial-recognition": {
                            "detection": {"modelName": "buffalo_l", "options": {"minScore": 0.034}},
                            "recognition": {"modelName": "buffalo_l"},
                        }
                    }
                )
            },
            files={"image": byte_image.getvalue()},
        )
        actual = response.json()
        assert response.status_code == 200
-        assert len(expected) == len(actual)
+        assert isinstance(actual, dict)
-        for expected_face, actual_face in zip(expected, actual):
+        assert actual.get("imageHeight", None) == responses["imageHeight"]
-            assert expected_face["imageHeight"] == actual_face["imageHeight"]
+        assert actual.get("imageWidth", None) == responses["imageWidth"]
-            assert expected_face["imageWidth"] == actual_face["imageWidth"]
+        assert "facial-recognition" in actual and isinstance(actual["facial-recognition"], list)
        assert len(actual["facial-recognition"]) == len(responses["facial-recognition"])
        for expected_face, actual_face in zip(responses["facial-recognition"], actual["facial-recognition"]):
            assert expected_face["boundingBox"] == actual_face["boundingBox"]
            assert np.allclose(expected_face["embedding"], actual_face["embedding"])
            assert np.allclose(expected_face["score"], actual_face["score"])
@@ -1,4 +1,4 @@
-FROM mambaorg/micromamba:bookworm-slim@sha256:d889b18dcb737911bb2628a649bcbd0dc42556148b0ece298021343bc66cf84a as builder
+FROM mambaorg/micromamba:bookworm-slim@sha256:4688551ffd61358d5bebfd88e0aac12d5b4aed7a153c170dbc435da453476a13 as builder
 ENV TRANSFORMERS_CACHE=/cache \
  PYTHONDONTWRITEBYTECODE=1 \
@@ -37,7 +37,6 @@ def on_test_start(environment: Environment, **kwargs: Any) -> None:
    global byte_image
    assert environment.parsed_options is not None
    image = Image.new("RGB", (environment.parsed_options.image_size, environment.parsed_options.image_size))
    byte_image = BytesIO()
    image.save(byte_image, format="jpeg")
@@ -45,34 +44,25 @@ class InferenceLoadTest(HttpUser):
    abstract: bool = True
    host = "http://127.0.0.1:3003"
    data: bytes
    headers: dict[str, str] = {"Content-Type": "image/jpg"}
    # re-use the image across all instances in a process
    def on_start(self) -> None:
        global byte_image
        self.data = byte_image.getvalue()
 class CLIPTextFormDataLoadTest(InferenceLoadTest):
    @task
    def encode_text(self) -> None:
-        data = [
+        request = {"clip": {"textual": {"modelName": self.environment.parsed_options.clip_model}}}
-            ("modelName", self.environment.parsed_options.clip_model),
+        data = [("entries", json.dumps(request)), ("text", "test search query")]
            ("modelType", "clip"),
            ("options", json.dumps({"mode": "text"})),
            ("text", "test search query"),
        ]
        self.client.post("/predict", data=data)
 class CLIPVisionFormDataLoadTest(InferenceLoadTest):
    @task
    def encode_image(self) -> None:
-        data = [
+        request = {"clip": {"visual": {"modelName": self.environment.parsed_options.clip_model, "options": {}}}}
-            ("modelName", self.environment.parsed_options.clip_model),
+        data = [("entries", json.dumps(request))]
            ("modelType", "clip"),
            ("options", json.dumps({"mode": "vision"})),
        ]
        files = {"image": self.data}
        self.client.post("/predict", data=data, files=files)
@@ -80,11 +70,18 @@ class CLIPVisionFormDataLoadTest(InferenceLoadTest):
 class RecognitionFormDataLoadTest(InferenceLoadTest):
    @task
    def recognize(self) -> None:
-        data = [
+        request = {
-            ("modelName", self.environment.parsed_options.face_model),
+            "facial-recognition": {
-            ("modelType", "facial-recognition"),
+                "recognition": {
-            ("options", json.dumps({"minScore": self.environment.parsed_options.face_min_score})),
+                    "modelName": self.environment.parsed_options.face_model,
-        ]
+                    "options": {"minScore": self.environment.parsed_options.face_min_score},
                },
                "detection": {
                    "modelName": self.environment.parsed_options.face_model,
                },
            }
        }
        data = [("entries", json.dumps(request))]
        files = {"image": self.data}
        self.client.post("/predict", data=data, files=files)
@@ -1236,13 +1236,13 @@ socks = ["socksio (==1.*)"]
 [[package]]
 name = "huggingface-hub"
-version = "0.23.2"
+version = "0.23.3"
 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 = [
-    {file = "huggingface_hub-0.23.2-py3-none-any.whl", hash = "sha256:48727a16e704d409c4bb5913613308499664f22a99743435dc3a13b23c485827"},
+    {file = "huggingface_hub-0.23.3-py3-none-any.whl", hash = "sha256:22222c41223f1b7c209ae5511d2d82907325a0e3cdbce5f66949d43c598ff3bc"},
-    {file = "huggingface_hub-0.23.2.tar.gz", hash = "sha256:f6829b62d5fdecb452a76fdbec620cba4c1573655a8d710c1df71735fd9edbd2"},
+    {file = "huggingface_hub-0.23.3.tar.gz", hash = "sha256:1a1118a0b3dea3bab6c325d71be16f5ffe441d32f3ac7c348d6875911b694b5b"},
 ]
 [package.dependencies]
@@ -2000,21 +2000,21 @@ sympy = "*"
 [[package]]
 name = "onnxruntime-gpu"
-version = "1.17.1"
+version = "1.18.0"
 description = "ONNX Runtime is a runtime accelerator for Machine Learning models"
 optional = false
 python-versions = "*"
 files = [
-    {file = "onnxruntime_gpu-1.17.1-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:e34ecb2b527ee1265135ae74cd99ea198ff344b8221929a920596a1e461e2bbb"},
+    {file = "onnxruntime_gpu-1.18.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:039be9a6b7f71c6739e97eec79f4bf240793a7c0c4108a09e0e1a27b4c33dbca"},
-    {file = "onnxruntime_gpu-1.17.1-cp310-cp310-win_amd64.whl", hash = "sha256:37786c0f225be90da0a66ca413fe125a925a0900263301cc4dbcad4ff0404673"},
+    {file = "onnxruntime_gpu-1.18.0-cp310-cp310-win_amd64.whl", hash = "sha256:afd4bc090b9412ab695cb34c05f4f92f88dbb6bd52d9b38658ad0115c50ff653"},
-    {file = "onnxruntime_gpu-1.17.1-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:3bde190a683ec84ecf61bd390f3c275d388efe72404633df374c52c557ce6d4d"},
+    {file = "onnxruntime_gpu-1.18.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:2280f94c6be2717f010a73c30a94c2721af853c6b7110e83afa52d03de6614a8"},
-    {file = "onnxruntime_gpu-1.17.1-cp311-cp311-win_amd64.whl", hash = "sha256:5206c84caa770efcc2ca819f71ec007a244ed748ca04e7ff76b86df1a096d2c8"},
+    {file = "onnxruntime_gpu-1.18.0-cp311-cp311-win_amd64.whl", hash = "sha256:9e3b4e9a0171e53a71001805b9b0e1a98cbad5a413d795c0e132b0f058b386d6"},
-    {file = "onnxruntime_gpu-1.17.1-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:0396ec73de565a64509d96dff154f531f8da8023c191f771ceba47a3f4efc266"},
+    {file = "onnxruntime_gpu-1.18.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:546fbf2dcb7a2830ca69bde0c38665a88a9454e923ebb76bedf85eaed33a6f4a"},
-    {file = "onnxruntime_gpu-1.17.1-cp312-cp312-win_amd64.whl", hash = "sha256:8531d4a833c8e978c5ff1de7b3bcc4126bbe58ea71fae54ddce58fe8777cb136"},
+    {file = "onnxruntime_gpu-1.18.0-cp312-cp312-win_amd64.whl", hash = "sha256:24146aa670c45734d9b8583cd78bd790363bc8695a3808d129ec913186064e4c"},
-    {file = "onnxruntime_gpu-1.17.1-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:7b831f9eafd626f3d44955420a4b1b84f9ffcb987712a0ab6a37d1ee9f2f7a45"},
+    {file = "onnxruntime_gpu-1.18.0-cp38-cp38-manylinux_2_28_x86_64.whl", hash = "sha256:75884c51c2aa47c349de3b5485df7f9573e1b89c607dd55984d3fe40615ef002"},
-    {file = "onnxruntime_gpu-1.17.1-cp38-cp38-win_amd64.whl", hash = "sha256:a389334d3797519d4b12077db32b8764f1ce54374d0f89235edc04efe8bc192c"},
+    {file = "onnxruntime_gpu-1.18.0-cp38-cp38-win_amd64.whl", hash = "sha256:f3b00a7443252dbfbd18ff72bcc2f44066fad9128eaa29bff8b315a834241701"},
-    {file = "onnxruntime_gpu-1.17.1-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:27aeaa36385e459b3867577ed7f68c1756de79aa68f57141d4ae2a31c84f6a33"},
+    {file = "onnxruntime_gpu-1.18.0-cp39-cp39-manylinux_2_28_x86_64.whl", hash = "sha256:14f53bd74ad21c61fee55eca988758e5eec4c39450040c8986ec3a960cb127a8"},
-    {file = "onnxruntime_gpu-1.17.1-cp39-cp39-win_amd64.whl", hash = "sha256:8b46094ea348aff6c6494402ac4260e2d2aba0522ae13e1ae29d98a29384ed70"},
+    {file = "onnxruntime_gpu-1.18.0-cp39-cp39-win_amd64.whl", hash = "sha256:aea5c02b3a0ee6682214a61a2a0467773401b075afdcb41dc2ef595f41c2d185"},
 ]
 [package.dependencies]
@@ -2054,18 +2054,18 @@ sympy = "*"
 [[package]]
 name = "opencv-python-headless"
-version = "4.9.0.80"
+version = "4.10.0.82"
 description = "Wrapper package for OpenCV python bindings."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "opencv-python-headless-4.9.0.80.tar.gz", hash = "sha256:71a4cd8cf7c37122901d8e81295db7fb188730e33a0e40039a4e59c1030b0958"},
+    {file = "opencv-python-headless-4.10.0.82.tar.gz", hash = "sha256:de9e742c1b9540816fbd115b0b03841d41ed0c65566b0d7a5371f98b131b7e6d"},
-    {file = "opencv_python_headless-4.9.0.80-cp37-abi3-macosx_10_16_x86_64.whl", hash = "sha256:2ea8a2edc4db87841991b2fbab55fc07b97ecb602e0f47d5d485bd75cee17c1a"},
+    {file = "opencv_python_headless-4.10.0.82-cp37-abi3-macosx_11_0_arm64.whl", hash = "sha256:a09ed50ba21cc5bf5d436cb0e784ad09c692d6b1d1454252772f6c8f2c7b4088"},
-    {file = "opencv_python_headless-4.9.0.80-cp37-abi3-macosx_11_0_arm64.whl", hash = "sha256:e0ee54e27be493e8f7850847edae3128e18b540dac1d7b2e4001b8944e11e1c6"},
+    {file = "opencv_python_headless-4.10.0.82-cp37-abi3-macosx_12_0_x86_64.whl", hash = "sha256:977a5fd21e1fe0d3d2134887db4441f8725abeae95150126302f31fcd9f548fa"},
-    {file = "opencv_python_headless-4.9.0.80-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:57ce2865e8fec431c6f97a81e9faaf23fa5be61011d0a75ccf47a3c0d65fa73d"},
+    {file = "opencv_python_headless-4.10.0.82-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:db4ec6755838b0be12510bfc9ffb014779c612418f11f4f7e6f505c36124a3aa"},
-    {file = "opencv_python_headless-4.9.0.80-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:976656362d68d9f40a5c66f83901430538002465f7db59142784f3893918f3df"},
+    {file = "opencv_python_headless-4.10.0.82-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:10a37fa5276967ecf6eb297295b16b28b7a2eb3b568ca0ee469fb1a5954de298"},
-    {file = "opencv_python_headless-4.9.0.80-cp37-abi3-win32.whl", hash = "sha256:11e3849d83e6651d4e7699aadda9ec7ed7c38957cbbcb99db074f2a2d2de9670"},
+    {file = "opencv_python_headless-4.10.0.82-cp37-abi3-win32.whl", hash = "sha256:94736e9b322d13db4768fd35588ad5e8995e78e207263076bfbee18aac835ad5"},
-    {file = "opencv_python_headless-4.9.0.80-cp37-abi3-win_amd64.whl", hash = "sha256:a8056c2cb37cd65dfcdf4153ca16f7362afcf3a50d600d6bb69c660fc61ee29c"},
+    {file = "opencv_python_headless-4.10.0.82-cp37-abi3-win_amd64.whl", hash = "sha256:c1822fa23d1641c0249ed5eb906f4c385f7959ff1bd601a776d56b0c18914af4"},
 ]
 [package.dependencies]
@@ -2438,13 +2438,13 @@ files = [
 [[package]]
 name = "pytest"
-version = "8.2.1"
+version = "8.2.2"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pytest-8.2.1-py3-none-any.whl", hash = "sha256:faccc5d332b8c3719f40283d0d44aa5cf101cec36f88cde9ed8f2bc0538612b1"},
+    {file = "pytest-8.2.2-py3-none-any.whl", hash = "sha256:c434598117762e2bd304e526244f67bf66bbd7b5d6cf22138be51ff661980343"},
-    {file = "pytest-8.2.1.tar.gz", hash = "sha256:5046e5b46d8e4cac199c373041f26be56fdb81eb4e67dc11d4e10811fc3408fd"},
+    {file = "pytest-8.2.2.tar.gz", hash = "sha256:de4bb8104e201939ccdc688b27a89a7be2079b22e2bd2b07f806b6ba71117977"},
 ]
 [package.dependencies]
@@ -2799,28 +2799,28 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 [[package]]
 name = "ruff"
-version = "0.4.5"
+version = "0.4.8"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 [[package]]
@@ -3234,13 +3234,13 @@ zstd = ["zstandard (>=0.18.0)"]
 [[package]]
 name = "uvicorn"
-version = "0.29.0"
+version = "0.30.1"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "uvicorn-0.29.0-py3-none-any.whl", hash = "sha256:2c2aac7ff4f4365c206fd773a39bf4ebd1047c238f8b8268ad996829323473de"},
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+    {file = "uvicorn-0.30.1.tar.gz", hash = "sha256:d46cd8e0fd80240baffbcd9ec1012a712938754afcf81bce56c024c1656aece8"},
 ]
 [package.dependencies]
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "machine-learning"
-version = "1.105.1"
+version = "1.106.3"
 description = ""
 authors = ["Hau Tran <alex.tran1502@gmail.com>"]
 readme = "README.md"
@@ -213,8 +213,6 @@
  },
  "facial-recognition": [
    {
      "imageWidth": 600,
      "imageHeight": 800,
      "boundingBox": {
        "x1": 690.0,
        "y1": -89.0,
@@ -325,5 +323,7 @@
        -0.077056274, 0.002099529
      ]
    }
-  ]
+  ],
  "imageWidth": 600,
  "imageHeight": 800
 }
@@ -0,0 +1,17 @@
 #! /usr/bin/env node
 const { readFileSync, writeFileSync } = require('node:fs');
 const nextVersion = process.argv[2];
 if (!nextVersion) {
  console.log('Usage: archive-version.js <version>');
  process.exit(1);
 }
 const filename = './docs/static/archived-versions.json';
 const oldVersions = JSON.parse(readFileSync(filename));
 const newVersions = [
  { label: `v${nextVersion}`, url: `https://v${nextVersion}.archive.immich.app` },
  ...oldVersions,
 ];
 writeFileSync(filename, JSON.stringify(newVersions, null, 2) + '\n');
@@ -66,10 +66,12 @@ if [ "$CURRENT_SERVER" != "$NEXT_SERVER" ]; then
  npm --prefix server run build
  make open-api
  npm --prefix open-api/typescript-sdk version "$SERVER_PUMP"
-  npm --prefix web version "$SERVER_PUMP"
+  # TODO use $SERVER_PUMP once we pass 2.2.x
-  npm --prefix e2e version "$SERVER_PUMP"
+  npm --prefix cli version patch
  npm --prefix web i --package-lock-only
  npm --prefix cli i --package-lock-only
  npm --prefix web version "$SERVER_PUMP"
  npm --prefix web i --package-lock-only
  npm --prefix e2e version "$SERVER_PUMP"
  npm --prefix e2e i --package-lock-only
  poetry --directory machine-learning version "$SERVER_PUMP"
 fi
@@ -83,4 +85,6 @@ sed -i "s/version_number: \"$CURRENT_SERVER\"$/version_number: \"$NEXT_SERVER\"/
 sed -i "s/\"android\.injected\.version\.code\" => $CURRENT_MOBILE,/\"android\.injected\.version\.code\" => $NEXT_MOBILE,/" mobile/android/fastlane/Fastfile
 sed -i "s/^version: $CURRENT_SERVER+$CURRENT_MOBILE$/version: $NEXT_SERVER+$NEXT_MOBILE/" mobile/pubspec.yaml
 ./misc/release/archive-version.js "$NEXT_SERVER"
 echo "IMMICH_VERSION=v$NEXT_SERVER" >>"$GITHUB_ENV"
@@ -35,8 +35,8 @@ platform :android do
      task: 'bundle', 
      build_type: 'Release',
      properties: {
-        "android.injected.version.code" => 140,
+        "android.injected.version.code" => 143,
-        "android.injected.version.name" => "1.105.1",
+        "android.injected.version.name" => "1.106.3",
      }
    )
    upload_to_play_store(skip_upload_apk: true, skip_upload_images: true, skip_upload_screenshots: true, aab: '../build/app/outputs/bundle/release/app-release.aab')
@@ -5,17 +5,17 @@
-      <testcase classname="fastlane.lanes" name="0: default_platform" time="0.000374">
+      <testcase classname="fastlane.lanes" name="0: default_platform" time="0.000381">
      </testcase>
-      <testcase classname="fastlane.lanes" name="1: bundleRelease" time="84.292464">
+      <testcase classname="fastlane.lanes" name="1: bundleRelease" time="52.832426">
      </testcase>
-      <testcase classname="fastlane.lanes" name="2: upload_to_play_store" time="33.336934">
+      <testcase classname="fastlane.lanes" name="2: upload_to_play_store" time="27.616558">
      </testcase>
@@ -1,12 +1,12 @@
 {
-  "action_common_back": "Back",
+  "action_common_back": "خلف",
  "action_common_cancel": "يلغي",
-  "action_common_clear": "Clear",
+  "action_common_clear": "مسح",
-  "action_common_confirm": "Confirm",
+  "action_common_confirm": "تأكيد",
  "action_common_update": "تحديث",
  "add_to_album_bottom_sheet_added": "تمت الاضافة{album}",
  "add_to_album_bottom_sheet_already_exists": "موجودة مسبقا {album}",
-  "advanced_settings_log_level_title": "تسجيل مستوى: {}",
+  "advanced_settings_log_level_title": "Log level: {}",
  "advanced_settings_prefer_remote_subtitle": "تكون بعض الأجهزة بطيئة للغاية في تحميل الصور المصغرة من الأصول الموجودة على الجهاز. قم بتنشيط هذا الإعداد لتحميل الصور البعيدة بدلاً من ذلك.",
  "advanced_settings_prefer_remote_title": "تفضل الصور البعيدة",
  "advanced_settings_self_signed_ssl_subtitle": "Skips SSL certificate verification for the server endpoint. Required for self-signed certificates.",
@@ -18,11 +18,11 @@
  "album_info_card_backup_album_excluded": "مستبعد",
  "album_info_card_backup_album_included": "متضمنة",
  "album_thumbnail_card_item": "عنصر واحد",
-  "album_thumbnail_card_items": "{} عناصر",
+  "album_thumbnail_card_items": "{} items",
  "album_thumbnail_card_shared": " · . مشترك",
  "album_thumbnail_owned": "مملوكة",
-  "album_thumbnail_shared_by": "مشترك مع",
+  "album_thumbnail_shared_by": "Shared by {}",
-  "album_viewer_appbar_delete_confirm": "Are you sure you want to delete this album from your account?",
+  "album_viewer_appbar_delete_confirm": "هل أنت متأكد أنك تريد حذف هذا الألبوم من حسابك؟",
  "album_viewer_appbar_share_delete": "حذف الألبوم",
  "album_viewer_appbar_share_err_delete": "فشل في حذف الألبوم",
  "album_viewer_appbar_share_err_leave": "فشل في ترك الألبوم",
@@ -38,20 +38,20 @@
  "app_bar_signout_dialog_ok": "نعم",
  "app_bar_signout_dialog_title": "خروج",
  "archive_page_no_archived_assets": "لم يتم العثور على الأصول المؤرشفة",
-  "archive_page_title": "أرشيف ({})",
+  "archive_page_title": "Archive ({})",
  "asset_action_delete_err_read_only": "لا يمكن حذف الأصول ذات للقراءة فقط، وسوف يتم التخطي",
  "asset_action_share_err_offline": "لا يمكن جلب الأصول غير المتصلة بالإنترنت، وسوف يتم التخطي",
-  "asset_list_group_by_sub_title": "Group by",
+  "asset_list_group_by_sub_title": "تنظيم بواسطة",
  "asset_list_layout_settings_dynamic_layout_title": "تخطيط ديناميكي",
  "asset_list_layout_settings_group_automatically": "تلقائي",
  "asset_list_layout_settings_group_by": "مجموعة الأصول حسب",
  "asset_list_layout_settings_group_by_month": "شهر",
  "asset_list_layout_settings_group_by_month_day": "شهر + يوم",
-  "asset_list_layout_sub_title": "Layout",
+  "asset_list_layout_sub_title": "تصميم",
  "asset_list_settings_subtitle": "إعدادات تخطيط شبكة الصور",
  "asset_list_settings_title": "شبكة الصور",
-  "asset_viewer_settings_title": "Asset Viewer",
+  "asset_viewer_settings_title": "عارض الأصول",
-  "backup_album_selection_page_albums_device": "الألبومات الموجودة على الجهاز ({})",
+  "backup_album_selection_page_albums_device": "Albums on device ({})",
  "backup_album_selection_page_albums_tap": "انقر للتضمين، وانقر نقرًا مزدوجًا للاستثناء",
  "backup_album_selection_page_assets_scatter": "يمكن أن تنتشر الأصول عبر ألبومات متعددة. وبالتالي، يمكن تضمين الألبومات أو استبعادها أثناء عملية النسخ الاحتياطي.",
  "backup_album_selection_page_select_albums": "حدد الألبومات",
@@ -60,22 +60,22 @@
  "backup_all": "الجميع",
  "backup_background_service_backup_failed_message": "فشل في النسخ الاحتياطي للأصول. جارٍ إعادة المحاولة...",
  "backup_background_service_connection_failed_message": "فشل في الاتصال بالخادم. جارٍ إعادة المحاولة...",
-  "backup_background_service_current_upload_notification": "تحميل {}",
+  "backup_background_service_current_upload_notification": "Uploading {}",
  "backup_background_service_default_notification": "التحقق من الأصول الجديدة ...",
  "backup_background_service_error_title": "خطأ في النسخ الاحتياطي",
  "backup_background_service_in_progress_notification": "النسخ الاحتياطي للأصول الخاصة بك...",
-  "backup_background_service_upload_failure_notification": "فشل التحميل {}",
+  "backup_background_service_upload_failure_notification": "Failed to upload {}",
  "backup_controller_page_albums": "ألبومات احتياطية",
  "backup_controller_page_background_app_refresh_disabled_content": "قم بتمكين تحديث تطبيق الخلفية في الإعدادات > عام > تحديث تطبيق الخلفية لاستخدام النسخ الاحتياطي في الخلفية.",
  "backup_controller_page_background_app_refresh_disabled_title": "تم تعطيل تحديث التطبيق في الخلفية",
  "backup_controller_page_background_app_refresh_enable_button_text": "اذهب للاعدادات",
  "backup_controller_page_background_battery_info_link": "أرني كيف",
-  "backup_controller_page_background_battery_info_message": "للحصول على أفضل تجربة نسخ احتياطي في الخلفية، يرجى تعطيل أي تحسينات للبطارية تقيد نشاط الخلفية لـ Immich.\n\nنظرًا لأن هذا خاص بالجهاز، يرجى البحث عن المعلومات المطلوبة للشركة المصنعة لجهازك.",
+  "backup_controller_page_background_battery_info_message": "للحصول على أفضل تجربة نسخ احتياطي في الخلفية، يرجى تعطيل أي تحسينات للبطارية تقيد نشاط الخلفية لـ تطبيق.\n\nنظرًا لأن هذا خاص بالجهاز، يرجى البحث عن المعلومات المطلوبة للشركة المصنعة لجهازك.",
  "backup_controller_page_background_battery_info_ok": "نعم",
  "backup_controller_page_background_battery_info_title": "تحسين البطارية",
  "backup_controller_page_background_charging": "فقط أثناء الشحن",
  "backup_controller_page_background_configure_error": "فشل في تكوين خدمة الخلفية",
-  "backup_controller_page_background_delay": "تأخير النسخ الاحتياطي للأصول الجديدة: {}",
+  "backup_controller_page_background_delay": "Delay new assets backup: {}",
  "backup_controller_page_background_description": "قم بتشغيل خدمة الخلفية لإجراء نسخ احتياطي لأي أصول جديدة تلقائيًا دون الحاجة إلى فتح التطبيق",
  "backup_controller_page_background_is_off": "تم إيقاف النسخ الاحتياطي التلقائي للخلفية",
  "backup_controller_page_background_is_on": "النسخ الاحتياطي التلقائي للخلفية قيد التشغيل",
@@ -86,12 +86,12 @@
  "backup_controller_page_backup_selected": "المحدد: ",
  "backup_controller_page_backup_sub": "النسخ الاحتياطي للصور ومقاطع الفيديو",
  "backup_controller_page_cancel": "يلغي",
-  "backup_controller_page_created": "تم إنشاؤها على: {}",
+  "backup_controller_page_created": "Created on: {}",
  "backup_controller_page_desc_backup": "قم بتشغيل النسخ الاحتياطي الأمامي لتحميل الأصول الجديدة تلقائيًا إلى الخادم عند فتح التطبيق.",
  "backup_controller_page_excluded": "مستبعد: ",
-  "backup_controller_page_failed": "فشل ({})",
+  "backup_controller_page_failed": "Failed ({})",
-  "backup_controller_page_filename": "اسم الملف: {} [{}]",
+  "backup_controller_page_filename": "File name: {} [{}]",
-  "backup_controller_page_id": "رقم البطاقة: {}",
+  "backup_controller_page_id": "ID: {}",
  "backup_controller_page_info": "معلومات النسخ الاحتياطي",
  "backup_controller_page_none_selected": "لم يتم التحديد",
  "backup_controller_page_remainder": "بقية",
@@ -101,7 +101,7 @@
  "backup_controller_page_start_backup": "بدء النسخ الاحتياطي",
  "backup_controller_page_status_off": "النسخة الاحتياطية التلقائية غير فعالة",
  "backup_controller_page_status_on": "النسخة الاحتياطية التلقائية فعالة",
-  "backup_controller_page_storage_format": "{} من {} المستخدم",
+  "backup_controller_page_storage_format": "{} of {} used",
  "backup_controller_page_to_backup": "الألبومات  الاحتياطية",
  "backup_controller_page_total": "المجموع",
  "backup_controller_page_total_sub": "جميع الصور ومقاطع الفيديو الفريدة من ألبومات مختارة",
@@ -115,22 +115,22 @@
  "backup_manual_in_progress": "قيد التحميل حاول مره اخرى",
  "backup_manual_success": "نجاح",
  "backup_manual_title": "حالة التحميل",
-  "backup_options_page_title": "Backup options",
+  "backup_options_page_title": "خيارات النسخ الاحتياطي",
-  "cache_settings_album_thumbnails": "صور صفحة المكتبة ({} الأصول)",
+  "cache_settings_album_thumbnails": "Library page thumbnails ({} assets)",
  "cache_settings_clear_cache_button": "مسح ذاكرة التخزين المؤقت",
  "cache_settings_clear_cache_button_title": "يقوم بمسح ذاكرة التخزين المؤقت للتطبيق.سيؤثر هذا بشكل كبير على أداء التطبيق حتى إعادة بناء ذاكرة التخزين المؤقت.",
  "cache_settings_duplicated_assets_clear_button": "واضح",
  "cache_settings_duplicated_assets_subtitle": "الصور ومقاطع الفيديو اللتي تم تجاهلها المدرجة في التطبيق",
-  "cache_settings_duplicated_assets_title": "الأصول المكررة ({})",
+  "cache_settings_duplicated_assets_title": "Duplicated Assets ({})",
-  "cache_settings_image_cache_size": "حجم ذاكرة التخزين المؤقت للصور ({} الأصول)",
+  "cache_settings_image_cache_size": "Image cache size ({} assets)",
  "cache_settings_statistics_album": "مكتبه الصور المصغره",
-  "cache_settings_statistics_assets": " ({})أصول ",
+  "cache_settings_statistics_assets": "{} assets ({})",
  "cache_settings_statistics_full": "صور كاملة",
  "cache_settings_statistics_shared": "صورة ألبوم مشتركة",
  "cache_settings_statistics_thumbnail": "الصورة المصغرة",
  "cache_settings_statistics_title": "استخدام ذاكرة التخزين المؤقت",
-  "cache_settings_subtitle": "تحكم في سلوك التخزين المؤقت لتطبيق الجوال Imich",
+  "cache_settings_subtitle": "تحكم في سلوك التخزين المؤقت لتطبيق الجوال.",
-  "cache_settings_thumbnail_size": "حجم ذاكرة التخزين المؤقت Thumbnail ({} الأصول)",
+  "cache_settings_thumbnail_size": "Thumbnail cache size ({} assets)",
  "cache_settings_tile_subtitle": "التحكم في سلوك التخزين المحلي",
  "cache_settings_tile_title": "التخزين المحلي",
  "cache_settings_title": "إعدادات التخزين المؤقت",
@@ -145,12 +145,12 @@
  "common_server_error": "يرجى التحقق من اتصال الشبكة الخاص بك ، والتأكد من أن الجهاز قابل للوصول وإصدارات التطبيق/الجهاز متوافقة.",
  "common_shared": "مشترك",
  "control_bottom_app_bar_add_to_album": "أضف إلى الألبوم",
-  "control_bottom_app_bar_album_info": "{} أغراض",
+  "control_bottom_app_bar_album_info": "{} items",
-  "control_bottom_app_bar_album_info_shared": "{} العناصر المشتركة",
+  "control_bottom_app_bar_album_info_shared": "{} items · Shared",
  "control_bottom_app_bar_archive": "أرشيف",
  "control_bottom_app_bar_create_new_album": "إنشاء ألبوم جديد",
  "control_bottom_app_bar_delete": "يمسح",
-  "control_bottom_app_bar_delete_from_immich": " Immich حذف منال تطبيق",
+  "control_bottom_app_bar_delete_from_immich": " حذف منال تطبيق",
  "control_bottom_app_bar_delete_from_local": "حذف من الجهاز",
  "control_bottom_app_bar_edit_location": "تحديد الوجهة",
  "control_bottom_app_bar_edit_time": "تحرير التاريخ والوقت",
@@ -172,10 +172,10 @@
  "daily_title_text_date": "E ، MMM DD",
  "daily_title_text_date_year": "E ، MMM DD ، yyyy",
  "date_format": "E ، Lll D ، Y • H: MM A",
-  "delete_dialog_alert": " Immich هذه العناصر سيتم حذفها بشكل دائم من جهازك ومن تطبيق",
+  "delete_dialog_alert": " هذه العناصر سيتم حذفها بشكل دائم من جهازك ومن تطبيق",
-  "delete_dialog_alert_local": " Immich العناصر التي تم حذفها من جهازك ولكنها موجوده في تطبيق",
+  "delete_dialog_alert_local": " العناصر التي تم حذفها من جهازك ولكنها موجوده في تطبيق",
-  "delete_dialog_alert_local_non_backed_up": "Immich بعض العناصر التي سيتم حذفها بشكل دائم ولا يوجد لها نسخه احتياطيه في تطبيق ",
+  "delete_dialog_alert_local_non_backed_up": "بعض العناصر التي سيتم حذفها بشكل دائم ولا يوجد لها نسخه احتياطيه في تطبيق ",
-  "delete_dialog_alert_remote": "Immich العناصر التي سيتم حذفها بشكل دائم من تطبيق",
+  "delete_dialog_alert_remote": "العناصر التي سيتم حذفها بشكل دائم من تطبيق",
  "delete_dialog_cancel": "يلغي",
  "delete_dialog_ok": "يمسح",
  "delete_dialog_ok_force": "احذف على أي حال",
@@ -194,15 +194,15 @@
  "exif_bottom_sheet_location": "موقع",
  "exif_bottom_sheet_location_add": "إضافة موقع",
  "exif_bottom_sheet_people": "الناس",
-  "exif_bottom_sheet_person_add_person": "Add name",
+  "exif_bottom_sheet_person_add_person": "اضف اسما",
  "experimental_settings_new_asset_list_subtitle": "أعمال جارية",
  "experimental_settings_new_asset_list_title": "تمكين شبكة الصور التجريبية",
  "experimental_settings_subtitle": "استخدام على مسؤوليتك الخاصة!",
  "experimental_settings_title": "تجريبي",
  "favorites_page_no_favorites": "لم يتم العثور على الأصول المفضلة",
  "favorites_page_title": "المفضلة",
-  "haptic_feedback_switch": "Enable haptic feedback",
+  "haptic_feedback_switch": "تمكين ردود الفعل اللمسية",
-  "haptic_feedback_title": "Haptic Feedback",
+  "haptic_feedback_title": "ردود فعل لمسية",
  "home_page_add_to_album_conflicts": "تمت إضافة {تمت إضافة} الأصول إلى الألبوم {الألبوم}.{فشل} الأصول موجودة بالفعل في الألبوم.",
  "home_page_add_to_album_err_local": "لا يمكن إضافة الأصول المحلية إلى الألبومات حتى الآن ، سوف يتخطى",
  "home_page_add_to_album_success": "تمت إضافة {تمت إضافة} الأصول إلى الألبوم {الألبوم}.",
@@ -218,7 +218,7 @@
  "home_page_share_err_local": "لا يمكن مشاركة الأصول المحلية عبر الرابط ، سوف يتخطى",
  "home_page_upload_err_limit": "لا يمكن إلا تحميل 30 أحد الأصول في وقت واحد ، سوف يتخطى",
  "image_viewer_page_state_provider_download_error": "خطا في التحميل",
-  "image_viewer_page_state_provider_download_started": "Download Started",
+  "image_viewer_page_state_provider_download_started": "بدأ التنزيل",
  "image_viewer_page_state_provider_download_success": "تم التنزيل بنجاح",
  "image_viewer_page_state_provider_share_error": "خطأ في المشاركة",
  "library_page_albums": "ألبومات",
@@ -265,8 +265,8 @@
  "login_form_server_error": "لا يمكن الاتصال بالخادم.",
  "login_password_changed_error": "كان هناك خطأ في تحديث كلمة المرور الخاصة بك",
  "login_password_changed_success": "تم تحديث كلمة السر بنجاح",
-  "map_assets_in_bound": "{} صورة",
+  "map_assets_in_bound": "{} photo",
-  "map_assets_in_bounds": "{} الصور",
+  "map_assets_in_bounds": "{} photos",
  "map_cannot_get_user_location": "لا يمكن الحصول على موقع المستخدم",
  "map_location_dialog_cancel": "يلغي",
  "map_location_dialog_yes": "نعم",
@@ -279,27 +279,27 @@
  "map_settings_dark_mode": "الوضع المظلم",
  "map_settings_date_range_option_all": "الجميع",
  "map_settings_date_range_option_day": "24 ساعة الماضية",
-  "map_settings_date_range_option_days": "الأيام الماضية {}",
+  "map_settings_date_range_option_days": "Past {} days",
  "map_settings_date_range_option_year": "السنة الفائتة",
-  "map_settings_date_range_option_years": "السنوات الماضية {}",
+  "map_settings_date_range_option_years": "Past {} years",
  "map_settings_dialog_cancel": "يلغي",
  "map_settings_dialog_save": "يحفظ",
  "map_settings_dialog_title": "إعدادات الخريطة",
  "map_settings_include_show_archived": "تشمل الأرشفة",
-  "map_settings_include_show_partners": "Include Partners",
+  "map_settings_include_show_partners": "تضمين الشركاء",
  "map_settings_only_relative_range": "نطاق الموعد",
  "map_settings_only_show_favorites": "اظهار المفضلة فقط",
  "map_settings_theme_settings": "مظهر الخريطة",
  "map_zoom_to_see_photos": "قم بتصغيرها لرؤية الصور",
-  "memories_all_caught_up": "All caught up",
+  "memories_all_caught_up": "كل شيء محدث",
-  "memories_check_back_tomorrow": "Check back tomorrow for more memories",
+  "memories_check_back_tomorrow": "التحقق مرة أخرى غدا لمزيد من الذكريات",
-  "memories_start_over": "Start Over",
+  "memories_start_over": "ابدأ من جديد",
-  "memories_swipe_to_close": "Swipe up to close",
+  "memories_swipe_to_close": "اسحب لأعلى للإغلاق",
  "monthly_title_text_date_format": "ط ط ط",
  "motion_photos_page_title": "الصور المتحركة",
  "multiselect_grid_edit_date_time_err_read_only": "لا يمكن تعديل تاريخ الأصول (المواد) للقراءة فقط، سوف يتخطى",
  "multiselect_grid_edit_gps_err_read_only": "لا يمكن تعديل موقع الأصول (المواد) للقراءة فقط، سوف يتخطى",
-  "no_assets_to_show": "No assets to show",
+  "no_assets_to_show": "لا توجد أصول لعرضها",
  "notification_permission_dialog_cancel": "يلغي",
  "notification_permission_dialog_content": "لتمكين الإخطارات ، انتقل إلى الإعدادات و اختار السماح.",
  "notification_permission_dialog_settings": "إعدادات",
@@ -307,14 +307,14 @@
  "notification_permission_list_tile_enable_button": "تمكين الإخطارات",
  "notification_permission_list_tile_title": "إذن الإخطار",
  "partner_list_user_photos": "{user}'s photos",
-  "partner_list_view_all": "View all",
+  "partner_list_view_all": "عرض الكل",
  "partner_page_add_partner": "أضف شريكًا",
  "partner_page_empty_message": "لم يتم مشاركة صورك بعد مع أي شريك.",
  "partner_page_no_more_users": "لا مزيد من المستخدمين لإضافة",
  "partner_page_partner_add_failed": "فشل في إضافة شريك",
  "partner_page_select_partner": "حدد شريكًا",
  "partner_page_shared_to_title": "مشترك ل",
-  "partner_page_stop_sharing_content": "{} لن يكون قادرًا على الوصول إلى صورك.",
+  "partner_page_stop_sharing_content": "{} will no longer be able to access your photos.",
  "partner_page_stop_sharing_title": "توقف عن مشاركة صورك؟",
  "partner_page_title": "شريك",
  "permission_onboarding_back": "خلف",
@@ -327,7 +327,7 @@
  "permission_onboarding_permission_granted": "تم تأمين التصريح! وضعك تمام.",
  "permission_onboarding_permission_limited": "إذن محدود. للسماح بالنسخ الاحتياطي للتطبيق وإدارة مجموعة المعرض بالكامل، امنح أذونات الصور والفيديو في الإعدادات.",
  "permission_onboarding_request": "يتطلب التطبيق إذنًا لعرض الصور ومقاطع الفيديو الخاصة بك",
-  "preferences_settings_title": "Preferences",
+  "preferences_settings_title": "التفضيلات",
  "profile_drawer_app_logs": "السجلات",
  "profile_drawer_client_out_of_date_major": "تطبيق الهاتف المحمول قديم.يرجى التحديث إلى أحدث إصدار رئيسي.",
  "profile_drawer_client_out_of_date_minor": "تطبيق الهاتف المحمول قديم.يرجى التحديث إلى أحدث إصدار صغير.",
@@ -342,18 +342,18 @@
  "recently_added_page_title": "أضيف مؤخرا",
  "scaffold_body_error_occurred": "حدث خطأ",
  "search_bar_hint": "ابحث عن صورك",
-  "search_filter_apply": "Apply filter",
+  "search_filter_apply": "اختار الفلتر ",
-  "search_filter_camera_make": "Make",
+  "search_filter_camera_make": "صنع",
-  "search_filter_camera_model": "Model",
+  "search_filter_camera_model": "نموذج",
-  "search_filter_display_option_archive": "Archive",
+  "search_filter_display_option_archive": "أرشيف",
-  "search_filter_display_option_favorite": "Favorite",
+  "search_filter_display_option_favorite": "مفضل",
-  "search_filter_display_option_not_in_album": "Not in album",
+  "search_filter_display_option_not_in_album": "ليس في الألبوم",
-  "search_filter_location_city": "City",
+  "search_filter_location_city": "مدينة",
-  "search_filter_location_country": "Country",
+  "search_filter_location_country": "دولة",
-  "search_filter_location_state": "State",
+  "search_filter_location_state": "ولاية",
-  "search_filter_media_type_all": "All",
+  "search_filter_media_type_all": "الجميع",
-  "search_filter_media_type_image": "Image",
+  "search_filter_media_type_image": "صورة",
-  "search_filter_media_type_video": "Video",
+  "search_filter_media_type_video": "شريط فيديو",
  "search_page_categories": "فئات",
  "search_page_favorites": "المفضلة",
  "search_page_motion_photos": "الصور المتحركه",
@@ -391,14 +391,15 @@
  "setting_image_viewer_original_title": "تحميل الصورة الأصلية",
  "setting_image_viewer_preview_subtitle": "تمكين تحميل صورة متوسطة الدقة.تعطيل إما لتحميل مباشرة أو استخدام الصورة المصغرة مباشرة.",
  "setting_image_viewer_preview_title": "تحميل صورة معاينة",
-  "setting_languages_apply": "Apply",
+  "setting_image_viewer_title": "الصور",
-  "setting_languages_title": "Languages",
+  "setting_languages_apply": "تغيير الإعدادات",
-  "setting_notifications_notify_failures_grace_period": "أخطر فشل النسخ الاحتياطي في الخلفية: {}",
+  "setting_languages_title": "اللغات",
-  "setting_notifications_notify_hours": "{} ساعات",
+  "setting_notifications_notify_failures_grace_period": "Notify background backup failures: {}",
  "setting_notifications_notify_hours": "{} hours",
  "setting_notifications_notify_immediately": "في الحال",
-  "setting_notifications_notify_minutes": "{} دقائق",
+  "setting_notifications_notify_minutes": "{} minutes",
  "setting_notifications_notify_never": "أبداً",
-  "setting_notifications_notify_seconds": "{} ثانية",
+  "setting_notifications_notify_seconds": "{} seconds",
  "setting_notifications_single_progress_subtitle": "معلومات التقدم التفصيلية تحميل لكل أصل",
  "setting_notifications_single_progress_title": "إظهار تقدم التفاصيل الاحتياطية الخلفية",
  "setting_notifications_subtitle": "اضبط تفضيلات الإخطار",
@@ -406,7 +407,10 @@
  "setting_notifications_total_progress_subtitle": "التقدم التحميل العام (تم القيام به/إجمالي الأصول)",
  "setting_notifications_total_progress_title": "إظهار النسخ الاحتياطي الخلفية التقدم المحرز",
  "setting_pages_app_bar_settings": "إعدادات",
-  "settings_require_restart": "يرجى إعادة تشغيل Imich لتطبيق هذا الإعداد",
+  "settings_require_restart": "يرجى إعادة تشغيل لتطبيق هذا الإعداد",
  "setting_video_viewer_looping_subtitle": "تمكين تكرار مقطع فيديو تلقائيًا في عارض التفاصيل.",
  "setting_video_viewer_looping_title": "تكرار مقطع فيديو تلقائيًا",
  "setting_video_viewer_title": "أشرطة فيديو",
  "share_add": "يضيف",
  "share_add_photos": "إضافة الصور",
  "share_add_title": "إضافة عنوان",
@@ -426,7 +430,7 @@
  "share_dialog_preparing": "تحضير...",
  "shared_link_app_bar_title": "روابط مشتركة",
  "shared_link_clipboard_copied_massage": "نسخ إلى الحافظة",
-  "shared_link_clipboard_text": "وصلة: {}كلمة المرور: {}",
+  "shared_link_clipboard_text": "Link: {}\nPassword: {}",
  "shared_link_create_app_bar_title": "إنشاء رابط للمشاركة",
  "shared_link_create_error": "خطأ أثناء إنشاء رابط مشترك",
  "shared_link_create_info": "دع أي شخص لديه الرابط يرى الصور المحددة)",
@@ -439,11 +443,11 @@
  "shared_link_edit_description_hint": "أدخل وصف المشاركة",
  "shared_link_edit_expire_after": "تنتهي بعد",
  "shared_link_edit_expire_after_option_day": "يوم 1",
-  "shared_link_edit_expire_after_option_days": "{} أيام",
+  "shared_link_edit_expire_after_option_days": "{} days",
  "shared_link_edit_expire_after_option_hour": "1 ساعة",
-  "shared_link_edit_expire_after_option_hours": "{} ساعات",
+  "shared_link_edit_expire_after_option_hours": "{} hours",
  "shared_link_edit_expire_after_option_minute": "1 دقيقة",
-  "shared_link_edit_expire_after_option_minutes": "{} دقائق",
+  "shared_link_edit_expire_after_option_minutes": "{} minutes",
  "shared_link_edit_expire_after_option_months": "{} months",
  "shared_link_edit_expire_after_option_never": "أبداً",
  "shared_link_edit_expire_after_option_year": "{} year",
@@ -454,21 +458,21 @@
  "shared_link_empty": "ليس لديك أي روابط مشتركة",
  "shared_link_error_server_url_fetch": "لا يمكن جلب عنوان الخادم",
  "shared_link_expired": "منتهي الصلاحية",
-  "shared_link_expires_day": "تنتهي في اليوم {}",
+  "shared_link_expires_day": "Expires in {} day",
-  "shared_link_expires_days": "تنتهي في {} أيام",
+  "shared_link_expires_days": "Expires in {} days",
-  "shared_link_expires_hour": "تنتهي في الساعة {}",
+  "shared_link_expires_hour": "Expires in {} hour",
-  "shared_link_expires_hours": "تنتهي في {} ساعات",
+  "shared_link_expires_hours": "Expires in {} hours",
-  "shared_link_expires_minute": "تنتهي في {} دقيقة",
+  "shared_link_expires_minute": "Expires in {} minute",
-  "shared_link_expires_minutes": "تنتهي في الدقائق {}",
+  "shared_link_expires_minutes": "Expires in {} minutes",
  "shared_link_expires_never": "تنتهي ∞",
-  "shared_link_expires_second": "تنتهي في {} الثاني",
+  "shared_link_expires_second": "Expires in {} second",
-  "shared_link_expires_seconds": "تنتهي في ثواني {}",
+  "shared_link_expires_seconds": "Expires in {} seconds",
  "shared_link_individual_shared": "Individual shared",
  "shared_link_info_chip_download": "تحميل",
  "shared_link_info_chip_metadata": "EXIF",
  "shared_link_info_chip_upload": "رفع",
  "shared_link_manage_links": "إدارة الروابط المشتركة",
-  "shared_link_public_album": "Public album",
+  "shared_link_public_album": "الألبوم العام",
  "share_done": "منتهي",
  "share_invite": "دعوة إلى الألبوم",
  "sharing_page_album": "ألبومات مشتركة",
@@ -482,7 +486,7 @@
  "tab_controller_nav_search": "يبحث",
  "tab_controller_nav_sharing": "مشاركة",
  "theme_setting_asset_list_storage_indicator_title": "عرض مؤشر التخزين على بلاط الأصول",
-  "theme_setting_asset_list_tiles_per_row_title": "عدد الأصول لكل صف ({})",
+  "theme_setting_asset_list_tiles_per_row_title": "Number of assets per row ({})",
  "theme_setting_dark_mode_switch": "الوضع المظلم",
  "theme_setting_image_viewer_quality_subtitle": "اضبط جودة عارض الصورة التفصيلية",
  "theme_setting_image_viewer_quality_title": "جودة عارض الصورة",
@@ -497,13 +501,13 @@
  "trash_page_empty_trash_btn": "افرغ سله المهملات ",
  "trash_page_empty_trash_dialog_content": "هل تريد تفريغ أصولك المهملة؟ ستتم إزالة هذه العناصر نهائيًا من التطبيق",
  "trash_page_empty_trash_dialog_ok": "نعم",
-  "trash_page_info": "سيتم حذف العناصر المحذوفة بشكل دائم بعد {} أيام",
+  "trash_page_info": "Trashed items will be permanently deleted after {} days",
  "trash_page_no_assets": "لا توجد اصول في سله المهملات",
  "trash_page_restore": "الترجيع من سله المهملات",
  "trash_page_restore_all": "استعادة الكل",
  "trash_page_select_assets_btn": "اختر الأصول ",
  "trash_page_select_btn": "يختار",
-  "trash_page_title": "نفايات ({})",
+  "trash_page_title": "Trash ({})",
  "upload_dialog_cancel": "يلغي",
  "upload_dialog_info": "هل تريد النسخ الاحتياطي للأصول (الأصول) المحددة إلى الخادم؟",
  "upload_dialog_ok": "رفع",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Načíst původní obrázek",
  "setting_image_viewer_preview_subtitle": "Umožňuje načíst obrázek se středním rozlišením. Zakažte, pokud chcete přímo načíst originál nebo použít pouze miniaturu.",
  "setting_image_viewer_preview_title": "Načíst náhled obrázku",
  "setting_image_viewer_title": "Obrázky",
  "setting_languages_apply": "Použít",
  "setting_languages_title": "Jazyk",
  "setting_notifications_notify_failures_grace_period": "Oznámení o selhání zálohování na pozadí: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Zobrazit celkový průběh zálohování na pozadí",
  "setting_pages_app_bar_settings": "Nastavení",
  "settings_require_restart": "Pro použití tohoto nastavení restartujte Immich",
  "setting_video_viewer_looping_subtitle": "Povolení automatické smyčky videa v prohlížeči detailů.",
  "setting_video_viewer_looping_title": "Smyčka",
  "setting_video_viewer_title": "Videa",
  "share_add": "Přidat",
  "share_add_photos": "Přidat fotografie",
  "share_add_title": "Přidat název",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Indlæs originalbillede",
  "setting_image_viewer_preview_subtitle": "Slå indlæsning af et mediumstørrelse billede til. Slå fra for enten direkte at indlæse originalen eller kun at bruge miniaturebilledet.",
  "setting_image_viewer_preview_title": "Indlæs forhåndsvisning af billedet",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Anvend",
  "setting_languages_title": "Sprog",
  "setting_notifications_notify_failures_grace_period": "Giv besked om fejl med sikkerhedskopiering i baggrunden: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Vis samlet baggrundsuploadstatus",
  "setting_pages_app_bar_settings": "Indstillinger",
  "settings_require_restart": "Genstart venligst Immich for at anvende denne ændring",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Tilføj",
  "share_add_photos": "Tilføj billeder",
  "share_add_title": "Tilføj en titel",
@@ -52,10 +52,10 @@
  "asset_list_settings_title": "Fotogitter",
  "asset_viewer_settings_title": "Fotoanzeige",
  "backup_album_selection_page_albums_device": "Alben auf dem Gerät ({})",
-  "backup_album_selection_page_albums_tap": "Einmalig tippen um einzuschließen, doppelt tippen um zu entfernen",
+  "backup_album_selection_page_albums_tap": "Einmalig tippen um das Album zu verwenden, doppelt tippen um es zu entfernen.",
-  "backup_album_selection_page_assets_scatter": "Elemente können sich über mehrere Alben verteilen. Daher können diese vor der Sicherung eingeschlossen oder ausgeschlossen werden",
+  "backup_album_selection_page_assets_scatter": "Elemente (Fotos / Videos) können sich über mehrere Alben verteilen. Daher können diese vor der Sicherung eingeschlossen oder ausgeschlossen werden.",
  "backup_album_selection_page_select_albums": "Alben auswählen",
-  "backup_album_selection_page_selection_info": "Auswahl",
+  "backup_album_selection_page_selection_info": "Information",
  "backup_album_selection_page_total_assets": "Elemente",
  "backup_all": "Alle",
  "backup_background_service_backup_failed_message": "Fehler beim Sichern von Elementen. Probiere erneut...",
@@ -75,7 +75,7 @@
  "backup_controller_page_background_battery_info_title": "Batterieoptimierungen",
  "backup_controller_page_background_charging": "Nur während des Ladens",
  "backup_controller_page_background_configure_error": "Konnte Hintergrundservice nicht konfigurieren",
-  "backup_controller_page_background_delay": "Sicherung neuer Elemente verzögern: {}",
+  "backup_controller_page_background_delay": "Sicherung neuer Elemente verzögern um: {}",
  "backup_controller_page_background_description": "Schalte den Hintergrundservice ein, um neue Elemente automatisch im Hintergrund zu sichern ohne die App zu öffnen",
  "backup_controller_page_background_is_off": "Automatische Sicherung im Hintergrund ist deaktiviert",
  "backup_controller_page_background_is_on": "Automatische Sicherung im Hintergrund ist aktiviert",
@@ -331,7 +331,7 @@
  "profile_drawer_app_logs": "Logs",
  "profile_drawer_client_out_of_date_major": "Mobile-App ist veraltet. Bitte aktualisiere auf die neueste Major-Version.",
  "profile_drawer_client_out_of_date_minor": "Mobile-App ist veraltet. Bitte aktualisiere auf die neueste Minor-Version.",
-  "profile_drawer_client_server_up_to_date": "App und Server sind aktuell",
+  "profile_drawer_client_server_up_to_date": "Die App-Version / Server-Version sind aktuell.",
  "profile_drawer_documentation": "Dokumentation",
  "profile_drawer_github": "GitHub",
  "profile_drawer_server_out_of_date_major": "Server-Version ist veraltet. Bitte aktualisiere auf die neueste Major-Version.",
@@ -382,19 +382,19 @@
  "select_additional_user_for_sharing_page_suggestions": "Vorschläge",
  "select_user_for_sharing_page_err_album": "Album konnte nicht erstellt werden",
  "select_user_for_sharing_page_share_suggestions": "Empfehlungen",
-  "server_info_box_app_version": "App Version",
+  "server_info_box_app_version": "App-Version",
  "server_info_box_latest_release": "Neueste Version",
  "server_info_box_server_url": "Server-URL",
-  "server_info_box_server_version": "Server Version",
+  "server_info_box_server_version": "Server-Version",
-  "setting_image_viewer_help": "Der Detailbildbetrachter lädt zuerst die kleine Miniaturansicht, dann die Vorschau in mittlerer Größe (falls aktiviert) und schließlich das Original (falls aktiviert).",
+  "setting_image_viewer_help": "Der Detailbildbetrachter lädt zuerst ein (kleines) Vorschaubild, dann ein Vorschaubild in mittlerer Größe (falls aktiviert) und schließlich das Original (falls aktiviert).",
  "setting_image_viewer_original_subtitle": "Aktivieren, um das Originalbild in voller Auflösung (groß!) zu laden. Deaktivieren, um den Datenverbrauch zu reduzieren (sowohl im Netzwerk als auch im Gerätespeicher).",
  "setting_image_viewer_original_title": "Original laden",
-  "setting_image_viewer_preview_subtitle": "Aktivieren, um ein Bild mit mittlerer Auflösung zu laden. Deaktivieren, um entweder das Original direkt zu laden oder nur die Miniaturansicht zu verwenden.",
+  "setting_image_viewer_preview_subtitle": "Aktivieren, um ein Bild mit mittlerer Auflösung zu laden. Deaktivieren, um entweder das Original direkt zu laden oder nur das Vorschaubild zu verwenden.",
  "setting_image_viewer_preview_title": "Vorschaubild laden",
  "setting_image_viewer_title": "Bilder",
  "setting_languages_apply": "Anwenden",
  "setting_languages_title": "Sprachen",
-  "setting_notifications_notify_failures_grace_period": "Benachrichtigung über Fehler bei der Hintergrundsicherung: {}",
+  "setting_notifications_notify_failures_grace_period": "Benachrichtigung bei Fehler/n in der Hintergrundsicherung: {}",
  "setting_notifications_notify_hours": "{} Stunden",
  "setting_notifications_notify_immediately": "sofort",
  "setting_notifications_notify_minutes": "{} Minuten",
@@ -407,10 +407,10 @@
  "setting_notifications_total_progress_subtitle": "Gesamter Upload-Fortschritt (abgeschlossen/Anzahl Elemente)",
  "setting_notifications_total_progress_title": "Zeige Gesamtfortschritt bei der Hintergrundsicherung",
  "setting_pages_app_bar_settings": "Einstellungen",
  "setting_video_viewer_looping_subtitle": "Aktivieren, damit sich ein Video in der Detailansicht automatisch wiederholt.",
  "setting_video_viewer_looping_title": "Wiederholen",
  "setting_video_viewer_title": "Videos",
  "settings_require_restart": "Bitte starte Immich neu, um diese Einstellung anzuwenden.",
  "setting_video_viewer_looping_subtitle": "Aktiviere diese Option, um ein Video in der Detailansicht automatisch in einer Schleife anzuzeigen.",
  "setting_video_viewer_looping_title": "Schleife / Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Hinzufügen",
  "share_add_photos": "Fotos hinzufügen",
  "share_add_title": "Titel hinzufügen",
@@ -485,12 +485,12 @@
  "tab_controller_nav_photos": "Fotos",
  "tab_controller_nav_search": "Suche",
  "tab_controller_nav_sharing": "Teilen",
-  "theme_setting_asset_list_storage_indicator_title": "Zeige Sicherungsstatus auf Miniaturbild",
+  "theme_setting_asset_list_storage_indicator_title": "Zeige Sicherungsstatus auf Vorschaubild",
  "theme_setting_asset_list_tiles_per_row_title": "Anzahl der Elemente pro Reihe ({})",
  "theme_setting_dark_mode_switch": "Dunkler Modus",
  "theme_setting_image_viewer_quality_subtitle": "Einstellen der Qualität des Detailbildbetrachters",
  "theme_setting_image_viewer_quality_title": "Qualität des Bildbetrachters",
-  "theme_setting_system_theme_switch": "Automatisch (Systemeinstellung folgen)",
+  "theme_setting_system_theme_switch": "Automatisch (Systemeinstellung)",
  "theme_setting_theme_subtitle": "Wählen Sie die Themeneinstellung der App",
  "theme_setting_theme_title": "Theme",
  "theme_setting_three_stage_loading_subtitle": "Das dreistufige Ladeverfahren kann die Performance beim Laden verbessern, erhöht allerdings den Datenverbrauch deutlich",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Load original image",
  "setting_image_viewer_preview_subtitle": "Enable to load a medium-resolution image. Disable to either directly load the original or only use the thumbnail.",
  "setting_image_viewer_preview_title": "Load preview image",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Apply",
  "setting_languages_title": "Languages",
  "setting_notifications_notify_failures_grace_period": "Notify background backup failures: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Show background backup total progress",
  "setting_pages_app_bar_settings": "Settings",
  "settings_require_restart": "Please restart Immich to apply this setting",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Add",
  "share_add_photos": "Add photos",
  "share_add_title": "Add a title",
@@ -102,7 +102,7 @@
  "backup_controller_page_status_off": "Automatic foreground backup is off",
  "backup_controller_page_status_on": "Automatic foreground backup is on",
  "backup_controller_page_storage_format": "{} of {} used",
-  "backup_controller_page_to_backup": "Albums to be backup",
+  "backup_controller_page_to_backup": "Albums to be backed up",
  "backup_controller_page_total": "Total",
  "backup_controller_page_total_sub": "All unique photos and videos from selected albums",
  "backup_controller_page_turn_off": "Turn off foreground backup",
@@ -407,10 +407,10 @@
  "setting_notifications_total_progress_subtitle": "Overall upload progress (done/total assets)",
  "setting_notifications_total_progress_title": "Show background backup total progress",
  "setting_pages_app_bar_settings": "Settings",
  "settings_require_restart": "Please restart Immich to apply this setting",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "settings_require_restart": "Please restart Immich to apply this setting",
  "share_add": "Add",
  "share_add_photos": "Add photos",
  "share_add_title": "Add a title",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Cargar imagen original",
  "setting_image_viewer_preview_subtitle": "Activar para cargar una imagen de resolución media. Deshabilitar para cargar directamente la imagen original o usar una miniatura.",
  "setting_image_viewer_preview_title": "Cargar imagen de previsualización",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Aplicar",
  "setting_languages_title": "Idiomas",
  "setting_notifications_notify_failures_grace_period": "Notificar fallos de copia de seguridad en segundo plano: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Mostrar progreso total de copia de seguridad en segundo plano",
  "setting_pages_app_bar_settings": "Ajustes",
  "settings_require_restart": "Por favor, reinicia Immich para aplicar este ajuste",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Agregar",
  "share_add_photos": "Agregar fotos",
  "share_add_title": "Agregar un título",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Cargar imagen original",
  "setting_image_viewer_preview_subtitle": "Activar para cargar una imagen de resolución media. Deshabilitar para cargar directamente la imagen original o usar una miniatura.",
  "setting_image_viewer_preview_title": "Cargar imagen de previsualización",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Apply",
  "setting_languages_title": "Languages",
  "setting_notifications_notify_failures_grace_period": "Notificar fallos de copia de seguridad en segundo plano: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Mostrar progreso total de copia de seguridad en segundo plano",
  "setting_pages_app_bar_settings": "Ajustes",
  "settings_require_restart": "Por favor, reinicia Immich para aplicar este ajuste",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Agregar",
  "share_add_photos": "Agregar fotos",
  "share_add_title": "Agregar un título",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Cargar imagen original",
  "setting_image_viewer_preview_subtitle": "Activar para cargar una imagen de resolución media. Deshabilitar para cargar directamente la imagen original o usar una miniatura.",
  "setting_image_viewer_preview_title": "Cargar imagen de previsualización",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Apply",
  "setting_languages_title": "Languages",
  "setting_notifications_notify_failures_grace_period": "Notificar fallos de copia de seguridad en segundo plano: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Mostrar progreso total de copia de seguridad en segundo plano",
  "setting_pages_app_bar_settings": "Ajustes",
  "settings_require_restart": "Por favor, reinicia Immich para aplicar este ajuste",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Agregar",
  "share_add_photos": "Agregar fotos",
  "share_add_title": "Agregar un título",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Cargar imagen original",
  "setting_image_viewer_preview_subtitle": "Activar para cargar una imagen de resolución media. Deshabilitar para cargar directamente la imagen original o usar una miniatura.",
  "setting_image_viewer_preview_title": "Cargar imagen de previsualización",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Apply",
  "setting_languages_title": "Languages",
  "setting_notifications_notify_failures_grace_period": "Notificar fallos de copia de seguridad en segundo plano: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Mostrar progreso total de copia de seguridad en segundo plano",
  "setting_pages_app_bar_settings": "Configuración",
  "settings_require_restart": "Por favor, reinicia Immich para aplicar este ajuste",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Agregar",
  "share_add_photos": "Agregar fotos",
  "share_add_title": "Agregar un título",
@@ -218,7 +218,7 @@
  "home_page_share_err_local": "Paikallisia kohteita ei voitu jakaa linkkien avulla. Hypätään yli",
  "home_page_upload_err_limit": "Voit lähettää palvelimelle enintään 30 kohdetta kerrallaan, ohitetaan",
  "image_viewer_page_state_provider_download_error": "Lataus epäonnistui",
-  "image_viewer_page_state_provider_download_started": "Download Started",
+  "image_viewer_page_state_provider_download_started": "Lataaminen aloitettu",
  "image_viewer_page_state_provider_download_success": "Lataus onnistui",
  "image_viewer_page_state_provider_share_error": "Jakovirhe",
  "library_page_albums": "Albumit",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Lataa alkuperäinen kuva",
  "setting_image_viewer_preview_subtitle": "Ota käyttöön ladataksesi keskitarkkuuksinen kuva. Poista käytöstä ladataksesi alkuperäinen kuva tai käyttääksesi vain esikatselukuvaa.",
  "setting_image_viewer_preview_title": "Lataa esikatselukuva",
  "setting_image_viewer_title": "Kuvat",
  "setting_languages_apply": "Käytä",
  "setting_languages_title": "Kieli",
  "setting_notifications_notify_failures_grace_period": "Ilmoita taustavarmuuskopioinnin epäonnistumisista: {}",
@@ -407,10 +408,13 @@
  "setting_notifications_total_progress_title": "Näytä taustavarmuuskopioinnin kokonaisedistyminen",
  "setting_pages_app_bar_settings": "Asetukset",
  "settings_require_restart": "Käynnistä Immich uudelleen ottaaksesti tämän asetuksen käyttöön",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videot",
  "share_add": "Lisää",
  "share_add_photos": "Lisää kuvia",
  "share_add_title": "Lisää nimi",
-  "share_assets_selected": "{} selected",
+  "share_assets_selected": "{} valittu",
  "share_create_album": "Luo albumi",
  "shared_album_activities_input_disable": "Kommentointi on kytketty pois päältä",
  "shared_album_activities_input_hint": "Sano jotain",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Charger l'image originale",
  "setting_image_viewer_preview_subtitle": "Activer pour charger une image de résolution moyenne. Désactiver pour charger directement l'original ou utiliser uniquement la vignette.",
  "setting_image_viewer_preview_title": "Charger l'image d'aperçu",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Apply",
  "setting_languages_title": "Languages",
  "setting_notifications_notify_failures_grace_period": "Notifier les échecs de la sauvegarde en arrière-plan: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Afficher la progression totale de la sauvegarde en arrière-plan",
  "setting_pages_app_bar_settings": "Paramètres",
  "settings_require_restart": "Veuillez redémarrer Immich pour appliquer ce paramètre",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Ajouter",
  "share_add_photos": "Ajouter des photos",
  "share_add_title": "Ajouter un titre",
@@ -1,8 +1,8 @@
 {
-  "action_common_back": "Back",
+  "action_common_back": "Retour",
  "action_common_cancel": "Annuler",
-  "action_common_clear": "Clear",
+  "action_common_clear": "Vider",
-  "action_common_confirm": "Confirm",
+  "action_common_confirm": "Confirmer",
  "action_common_update": "Mise à jour",
  "add_to_album_bottom_sheet_added": "Ajouté à {album}",
  "add_to_album_bottom_sheet_already_exists": "Déjà dans {album}",
@@ -22,7 +22,7 @@
  "album_thumbnail_card_shared": " · Partagé",
  "album_thumbnail_owned": "Possédé",
  "album_thumbnail_shared_by": "Partagé par {}",
-  "album_viewer_appbar_delete_confirm": "Are you sure you want to delete this album from your account?",
+  "album_viewer_appbar_delete_confirm": "Êtes-vous sur de vouloir supprimer cet album de votre compte?",
  "album_viewer_appbar_share_delete": "Supprimer l'album",
  "album_viewer_appbar_share_err_delete": "Échec de la suppression de l'album",
  "album_viewer_appbar_share_err_leave": "Impossible de quitter l'album",
@@ -41,7 +41,7 @@
  "archive_page_title": "Archive ({})",
  "asset_action_delete_err_read_only": "Impossible de supprimer le(s) élément(s) en lecture seule.",
  "asset_action_share_err_offline": "Impossible de récupérer le(s) élément(s) hors ligne.",
-  "asset_list_group_by_sub_title": "Groupe par",
+  "asset_list_group_by_sub_title": "Regrouper par",
  "asset_list_layout_settings_dynamic_layout_title": "Affichage dynamique",
  "asset_list_layout_settings_group_automatically": "Automatique",
  "asset_list_layout_settings_group_by": "Grouper les éléments par",
@@ -115,7 +115,7 @@
  "backup_manual_in_progress": "Téléchargement déjà en cours. Essayez après un instant",
  "backup_manual_success": "Succès ",
  "backup_manual_title": "Statut du téléchargement ",
-  "backup_options_page_title": "Backup options",
+  "backup_options_page_title": "Options de sauvegarde",
  "cache_settings_album_thumbnails": "Miniatures de la page bibliothèque ({} éléments)",
  "cache_settings_clear_cache_button": "Effacer le cache",
  "cache_settings_clear_cache_button_title": "Efface le cache de l'application. Cela aura un impact significatif sur les performances de l'application jusqu'à ce que le cache soit reconstruit.",
@@ -218,7 +218,7 @@
  "home_page_share_err_local": "Impossible de partager par lien les médias locaux, cette opération est donc ignorée.",
  "home_page_upload_err_limit": "Limite de téléchargement de 30 éléments en même temps, demande ignorée",
  "image_viewer_page_state_provider_download_error": "Erreur de téléchargement",
-  "image_viewer_page_state_provider_download_started": "Download Started",
+  "image_viewer_page_state_provider_download_started": "Téléchargement Démarré",
  "image_viewer_page_state_provider_download_success": "Téléchargement réussi",
  "image_viewer_page_state_provider_share_error": "Erreur de partage",
  "library_page_albums": "Albums",
@@ -286,7 +286,7 @@
  "map_settings_dialog_save": "Sauvegarder",
  "map_settings_dialog_title": "Paramètres de la carte",
  "map_settings_include_show_archived": "Inclure les archives",
-  "map_settings_include_show_partners": "Include Partners",
+  "map_settings_include_show_partners": "Inclure les partenaires",
  "map_settings_only_relative_range": "Plage de dates",
  "map_settings_only_show_favorites": "Afficher uniquement les favoris",
  "map_settings_theme_settings": "Thème de la carte",
@@ -299,15 +299,15 @@
  "motion_photos_page_title": "Photos avec mouvement",
  "multiselect_grid_edit_date_time_err_read_only": "Impossible de modifier la date d'un élément d'actif en lecture seule.",
  "multiselect_grid_edit_gps_err_read_only": "Impossible de modifier l'emplacement d'un élément en lecture seule.",
-  "no_assets_to_show": "Aucun élément à afficher",
+  "no_assets_to_show": "Aucuns éléments à afficher",
  "notification_permission_dialog_cancel": "Annuler",
  "notification_permission_dialog_content": "Pour activer les notifications, allez dans Paramètres et sélectionnez Autoriser.",
  "notification_permission_dialog_settings": "Paramètres",
  "notification_permission_list_tile_content": "Accordez la permission d'activer les notifications.",
  "notification_permission_list_tile_enable_button": "Activer les notifications",
  "notification_permission_list_tile_title": "Permission de notification",
-  "partner_list_user_photos": "{user}'s photos",
+  "partner_list_user_photos": "Photos de {user}",
-  "partner_list_view_all": "View all",
+  "partner_list_view_all": "Voir tous",
  "partner_page_add_partner": "Ajouter un partenaire",
  "partner_page_empty_message": "Vos photos ne sont pas encore partagées avec un partenaire.",
  "partner_page_no_more_users": "Plus d'utilisateurs à ajouter",
@@ -342,18 +342,18 @@
  "recently_added_page_title": "Récemment ajouté",
  "scaffold_body_error_occurred": "Une erreur s'est produite",
  "search_bar_hint": "Rechercher vos photos",
-  "search_filter_apply": "Apply filter",
+  "search_filter_apply": "Appliquer le filtre",
-  "search_filter_camera_make": "Make",
+  "search_filter_camera_make": "Fabricant",
-  "search_filter_camera_model": "Model",
+  "search_filter_camera_model": "Modéle",
-  "search_filter_display_option_archive": "Archive",
+  "search_filter_display_option_archive": "Achive",
-  "search_filter_display_option_favorite": "Favorite",
+  "search_filter_display_option_favorite": "Favoris",
-  "search_filter_display_option_not_in_album": "Not in album",
+  "search_filter_display_option_not_in_album": "Pas dans un album",
-  "search_filter_location_city": "City",
+  "search_filter_location_city": "Ville",
-  "search_filter_location_country": "Country",
+  "search_filter_location_country": "Pays",
-  "search_filter_location_state": "State",
+  "search_filter_location_state": "Région",
-  "search_filter_media_type_all": "All",
+  "search_filter_media_type_all": "Tous",
  "search_filter_media_type_image": "Image",
-  "search_filter_media_type_video": "Video",
+  "search_filter_media_type_video": "Vidéo",
  "search_page_categories": "Catégories",
  "search_page_favorites": "Favoris",
  "search_page_motion_photos": "Photos animées",
@@ -391,8 +391,9 @@
  "setting_image_viewer_original_title": "Charger l'image originale",
  "setting_image_viewer_preview_subtitle": "Activer pour charger une image de résolution moyenne. Désactiver pour charger directement l'original ou utiliser uniquement la miniature.",
  "setting_image_viewer_preview_title": "Charger l'image d'aperçu",
-  "setting_languages_apply": "Apply",
+  "setting_image_viewer_title": "Images",
-  "setting_languages_title": "Languages",
+  "setting_languages_apply": "Appliquer",
  "setting_languages_title": "Langues",
  "setting_notifications_notify_failures_grace_period": "Notifier les échecs de la sauvegarde en arrière-plan : {}",
  "setting_notifications_notify_hours": "{} heures",
  "setting_notifications_notify_immediately": "immédiatement",
@@ -407,10 +408,13 @@
  "setting_notifications_total_progress_title": "Afficher la progression totale de la sauvegarde en arrière-plan",
  "setting_pages_app_bar_settings": "Paramètres",
  "settings_require_restart": "Veuillez redémarrer Immich pour appliquer ce paramètre",
  "setting_video_viewer_looping_subtitle": "Activer pour voir les vidéos en boucle dans le lecteur détaillé",
  "setting_video_viewer_looping_title": "Boucle",
  "setting_video_viewer_title": "Vidéos",
  "share_add": "Ajouter",
  "share_add_photos": "Ajouter des photos",
  "share_add_title": "Ajouter un titre",
-  "share_assets_selected": "{} selected",
+  "share_assets_selected": "{} séléctionné(s)",
  "share_create_album": "Créer un album",
  "shared_album_activities_input_disable": "Les commentaires sont désactivés",
  "shared_album_activities_input_hint": "Dire quelque chose",
@@ -444,9 +448,9 @@
  "shared_link_edit_expire_after_option_hours": "{} heures",
  "shared_link_edit_expire_after_option_minute": "1 minute",
  "shared_link_edit_expire_after_option_minutes": "{} minutes",
-  "shared_link_edit_expire_after_option_months": "{} months",
+  "shared_link_edit_expire_after_option_months": "{} mois",
  "shared_link_edit_expire_after_option_never": "Jamais",
-  "shared_link_edit_expire_after_option_year": "{} year",
+  "shared_link_edit_expire_after_option_year": "{} ans",
  "shared_link_edit_password": "Mot de passe",
  "shared_link_edit_password_hint": "Saisir le mot de passe de partage",
  "shared_link_edit_show_meta": "Afficher les métadonnées",
@@ -463,12 +467,12 @@
  "shared_link_expires_never": "Expire ∞",
  "shared_link_expires_second": "Expire dans {} seconde",
  "shared_link_expires_seconds": "Expire dans {} secondes",
-  "shared_link_individual_shared": "Individual shared",
+  "shared_link_individual_shared": "Partagé individuellement",
  "shared_link_info_chip_download": "Téléchargement",
  "shared_link_info_chip_metadata": "EXIF",
  "shared_link_info_chip_upload": "Chargement",
  "shared_link_manage_links": "Gérer les liens partagés",
-  "shared_link_public_album": "Public album",
+  "shared_link_public_album": "Album public",
  "share_done": "Fait",
  "share_invite": "Inviter à l'album",
  "sharing_page_album": "Albums partagés",
@@ -82,7 +82,7 @@
  "backup_controller_page_background_turn_off": "כבה שירות ברקע",
  "backup_controller_page_background_turn_on": "הפעל שירות ברקע",
  "backup_controller_page_background_wifi": "רק ברשת אלחוטית",
-  "backup_controller_page_backup": "גיבוי",
+  "backup_controller_page_backup": "גובו",
  "backup_controller_page_backup_selected": "נבחרו:",
  "backup_controller_page_backup_sub": "תמונות וסרטונים מגובים",
  "backup_controller_page_cancel": "ביטול",
@@ -94,7 +94,7 @@
  "backup_controller_page_id": "מזהה: {}",
  "backup_controller_page_info": "פרטי גיבוי",
  "backup_controller_page_none_selected": "לא נבחרו",
-  "backup_controller_page_remainder": "יתרה",
+  "backup_controller_page_remainder": "בתור לגיבוי",
  "backup_controller_page_remainder_sub": "תמונות וסרטונים שנותרו לגבות מתוך בחירה",
  "backup_controller_page_select": "בחר",
  "backup_controller_page_server_storage": "אחסון שרת",
@@ -107,7 +107,7 @@
  "backup_controller_page_total_sub": "כל התמונות והסרטונים הייחודיים מאלבומים שנבחרו",
  "backup_controller_page_turn_off": "כבה גיבוי חזית",
  "backup_controller_page_turn_on": "הפעל גיבוי חזית",
-  "backup_controller_page_uploading_file_info": "מעלה פרטי קובץ",
+  "backup_controller_page_uploading_file_info": "מידע על הקובץ",
  "backup_err_only_album": "לא ניתן להסיר את האלבום היחידי",
  "backup_info_card_assets": "נכסים",
  "backup_manual_cancelled": "בוטל",
@@ -218,7 +218,7 @@
  "home_page_share_err_local": "לא ניתן לשתף נכסים מקומיים על ידי קישור, מדלג",
  "home_page_upload_err_limit": "יכול רק להעלות מקסימום של 30 נכסים בכל פעם, מדלג",
  "image_viewer_page_state_provider_download_error": "שגיאת הורדה",
-  "image_viewer_page_state_provider_download_started": "Download Started",
+  "image_viewer_page_state_provider_download_started": "ההורדה החלה",
  "image_viewer_page_state_provider_download_success": "הצלחת הורדה",
  "image_viewer_page_state_provider_share_error": "שיתוף שגיאה",
  "library_page_albums": "אלבומים",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "טען תמונה מקורית",
  "setting_image_viewer_preview_subtitle": "אפשר לטעון תמונה ברזלוציה בינונית. השבת כדי או לטעון את המקורית או רק להשתמש בתמונה הממוזערת.",
  "setting_image_viewer_preview_title": "טען תמונת תצוגה מקדימה",
  "setting_image_viewer_title": "תמונות",
  "setting_languages_apply": "החל",
  "setting_languages_title": "שפות",
  "setting_notifications_notify_failures_grace_period": "להודיע על כשלים בגיבוי ברקע: {}",
@@ -407,10 +408,13 @@
  "setting_notifications_total_progress_title": "הראה סה״כ התקדמות גיבוי ברקע",
  "setting_pages_app_bar_settings": "הגדרות",
  "settings_require_restart": "אנא הפעל מחדש את Immich כדי להחיל הגדרה זו",
  "setting_video_viewer_looping_subtitle": "אפשר וידיאו ברצף אוטומטית בחלון המידע",
  "setting_video_viewer_looping_title": "לולאה",
  "setting_video_viewer_title": "סרטונים",
  "share_add": "הוסף",
  "share_add_photos": "הוסף תמונות",
  "share_add_title": "הוסף כותרת",
-  "share_assets_selected": "{} selected",
+  "share_assets_selected": "{} נבחרו",
  "share_create_album": "צור אלבום",
  "shared_album_activities_input_disable": "התגובה מושבתת",
  "shared_album_activities_input_hint": "הגב/י משהו",
@@ -102,7 +102,7 @@
  "backup_controller_page_status_off": "Automatic foreground backup is off",
  "backup_controller_page_status_on": "Automatic foreground backup is on",
  "backup_controller_page_storage_format": "{} of {} used",
-  "backup_controller_page_to_backup": "Albums to be backup",
+  "backup_controller_page_to_backup": "Albums to be backed up",
  "backup_controller_page_total": "Total",
  "backup_controller_page_total_sub": "All unique photos and videos from selected albums",
  "backup_controller_page_turn_off": "Turn off foreground backup",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Load original image",
  "setting_image_viewer_preview_subtitle": "Enable to load a medium-resolution image. Disable to either directly load the original or only use the thumbnail.",
  "setting_image_viewer_preview_title": "Load preview image",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Apply",
  "setting_languages_title": "Languages",
  "setting_notifications_notify_failures_grace_period": "Notify background backup failures: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Show background backup total progress",
  "setting_pages_app_bar_settings": "Settings",
  "settings_require_restart": "Please restart Immich to apply this setting",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Add",
  "share_add_photos": "Add photos",
  "share_add_title": "Add a title",
@@ -194,7 +194,7 @@
  "exif_bottom_sheet_location": "HELY",
  "exif_bottom_sheet_location_add": "Hely hozzáadása",
  "exif_bottom_sheet_people": "EMBEREK",
-  "exif_bottom_sheet_person_add_person": "Név hozzáadása",
+  "exif_bottom_sheet_person_add_person": "Elnevez",
  "experimental_settings_new_asset_list_subtitle": "Fejlesztés alatt",
  "experimental_settings_new_asset_list_title": "Kisérleti képrács engedélyezése",
  "experimental_settings_subtitle": "Csak saját felelősségre használd!",
@@ -363,9 +363,9 @@
  "search_page_person_add_name_dialog_cancel": "Mégsem",
  "search_page_person_add_name_dialog_hint": "Név",
  "search_page_person_add_name_dialog_save": "Mentés",
-  "search_page_person_add_name_dialog_title": "Név hozzáadása",
+  "search_page_person_add_name_dialog_title": "Elnevez",
  "search_page_person_add_name_subtitle": "Név szerint gyorsan megtalálhatod a keresőben",
-  "search_page_person_add_name_title": "Név hozzáadása",
+  "search_page_person_add_name_title": "Elnevez",
  "search_page_person_edit_name": "Név módosítása",
  "search_page_places": "Helyek",
  "search_page_recently_added": "Nemrég hozzáadott",
@@ -374,8 +374,8 @@
  "search_page_things": "Dolgok",
  "search_page_videos": "Videók",
  "search_page_view_all_button": "Összes mutatása",
-  "search_page_your_activity": "Tevékenységeid",
+  "search_page_your_activity": "Tevékenységek",
-  "search_page_your_map": "Térképed",
+  "search_page_your_map": "Térkép",
  "search_result_page_new_search_hint": "Új keresés",
  "search_suggestion_list_smart_search_hint_1": "Az intelligens keresés alapértelmezetten be van kapcsolva, metaadatokat így kereshetsz",
  "search_suggestion_list_smart_search_hint_2": "m:keresési-kifejezés",
@@ -386,11 +386,12 @@
  "server_info_box_latest_release": "Legfrissebb Verzió",
  "server_info_box_server_url": "Szerver Címe",
  "server_info_box_server_version": "Szerver Verzió",
-  "setting_image_viewer_help": "A képnézegető először a kis bélyegképet tölti be, aztán a közepes méretű előnézetet (ha elérhető), végül az eredetit (ha elérhető).",
+  "setting_image_viewer_help": "Az Elem Megjelenítő először a kis bélyegképet tölti be, aztán a közepes méretű előnézetet (ha elérhető), végül az eredetit (ha elérhető).",
  "setting_image_viewer_original_subtitle": "Engedélyezi az eredeti teljes felbontású kép betöltését (nagy!). Kikapcsolva csökkenti az adathasználatot (a neten és az eszköz gyorsítótárán is).",
  "setting_image_viewer_original_title": "Eredeti kép betöltése",
  "setting_image_viewer_preview_subtitle": "Engedélyezi a közepes felbontású kép betöltését. Kikapcsolva vagy az eredeti kép töltődik be, vagy csak a bélyegkép.",
  "setting_image_viewer_preview_title": "Előnézet betöltése",
  "setting_image_viewer_title": "Képek",
  "setting_languages_apply": "Alkalmaz",
  "setting_languages_title": "Nyelvek",
  "setting_notifications_notify_failures_grace_period": "Értesítés a háttérben történő mentés hibáiról: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Mutassa a háttérben történő mentés teljes folyamatát",
  "setting_pages_app_bar_settings": "Beállítások",
  "settings_require_restart": "Ennek a beállításnak az érvénybe lépéséhez indítsd újra az Immich-et",
  "setting_video_viewer_looping_subtitle": "Engedélyezi a videók folyamatosan ismételt lejátszását az elem megjelenítőben",
  "setting_video_viewer_looping_title": "Ismétlés",
  "setting_video_viewer_title": "Videók",
  "share_add": "Hozzáadás",
  "share_add_photos": "Fotók hozzáadása",
  "share_add_title": "Album neve",
@@ -391,6 +391,7 @@
  "setting_image_viewer_original_title": "Carica l'immagine originale",
  "setting_image_viewer_preview_subtitle": "Abilita per caricare un'immagine a risoluzione media.\nDisabilita per caricare direttamente l'immagine originale o usare la thumbnail.",
  "setting_image_viewer_preview_title": "Carica immagine di anteprima",
  "setting_image_viewer_title": "Images",
  "setting_languages_apply": "Applica",
  "setting_languages_title": "Lingue",
  "setting_notifications_notify_failures_grace_period": "Notifica caricamenti falliti in background: {}",
@@ -407,6 +408,9 @@
  "setting_notifications_total_progress_title": "Mostra avanzamento del backup in background",
  "setting_pages_app_bar_settings": "Impostazioni",
  "settings_require_restart": "Si prega di riavviare Immich perché vengano applicate le impostazioni",
  "setting_video_viewer_looping_subtitle": "Enable to automatically loop a video in the detail viewer.",
  "setting_video_viewer_looping_title": "Looping",
  "setting_video_viewer_title": "Videos",
  "share_add": "Aggiungi",
  "share_add_photos": "Aggiungi foto",
  "share_add_title": "Aggiungi un titolo ",
--- a/Show More
+++ b/Show More