feat(ml)!: customizable ML settings (#3891)

* consolidated endpoints, added live configuration

* added ml settings to server

* added settings dashboard

* updated deps, fixed typos

* simplified modelconfig

updated tests

* Added ml setting accordion for admin page

updated tests

* merge `clipText` and `clipVision`

* added face distance setting

clarified setting

* add clip mode in request, dropdown for face models

* polished ml settings

updated descriptions

* update clip field on error

* removed unused import

* add description for image classification threshold

* pin safetensors for arm wheel

updated poetry lock

* moved dto

* set model type only in ml repository

* revert form-data package install

use fetch instead of axios

* added slotted description with link

updated facial recognition description

clarified effect of disabling tasks

* validation before model load

* removed unnecessary getconfig call

* added migration

* updated api

updated api

updated api

---------

Co-authored-by: Alex Tran <alex.tran1502@gmail.com>

cli/src/api/open-api/api.ts

@@ -862,6 +862,53 @@ export interface BulkIdsDto {
      */
     'ids': Array<string>;
 }
+/**
+ * 
+ * @export
+ * @interface CLIPConfig
+ */
+export interface CLIPConfig {
+    /**
+     * 
+     * @type {boolean}
+     * @memberof CLIPConfig
+     */
+    'enabled': boolean;
+    /**
+     * 
+     * @type {CLIPMode}
+     * @memberof CLIPConfig
+     */
+    'mode'?: CLIPMode;
+    /**
+     * 
+     * @type {string}
+     * @memberof CLIPConfig
+     */
+    'modelName': string;
+    /**
+     * 
+     * @type {ModelType}
+     * @memberof CLIPConfig
+     */
+    'modelType'?: ModelType;
+}
+
+
+/**
+ * 
+ * @export
+ * @enum {string}
+ */
+
+export const CLIPMode = {
+    Vision: 'vision',
+    Text: 'text'
+} as const;
+
+export type CLIPMode = typeof CLIPMode[keyof typeof CLIPMode];
+
+
 /**
  * 
  * @export
@@ -951,6 +998,39 @@ export interface CheckExistingAssetsResponseDto {
      */
     'existingIds': Array<string>;
 }
+/**
+ * 
+ * @export
+ * @interface ClassificationConfig
+ */
+export interface ClassificationConfig {
+    /**
+     * 
+     * @type {boolean}
+     * @memberof ClassificationConfig
+     */
+    'enabled': boolean;
+    /**
+     * 
+     * @type {number}
+     * @memberof ClassificationConfig
+     */
+    'minScore': number;
+    /**
+     * 
+     * @type {string}
+     * @memberof ClassificationConfig
+     */
+    'modelName': string;
+    /**
+     * 
+     * @type {ModelType}
+     * @memberof ClassificationConfig
+     */
+    'modelType'?: ModelType;
+}
+
+
 /**
  * 
  * @export
@@ -1766,6 +1846,21 @@ export interface MergePersonDto {
      */
     'ids': Array<string>;
 }
+/**
+ * 
+ * @export
+ * @enum {string}
+ */
+
+export const ModelType = {
+    ImageClassification: 'image-classification',
+    FacialRecognition: 'facial-recognition',
+    Clip: 'clip'
+} as const;
+
+export type ModelType = typeof ModelType[keyof typeof ModelType];
+
+
 /**
  * 
  * @export
@@ -1991,6 +2086,45 @@ export interface QueueStatusDto {
      */
     'isPaused': boolean;
 }
+/**
+ * 
+ * @export
+ * @interface RecognitionConfig
+ */
+export interface RecognitionConfig {
+    /**
+     * 
+     * @type {boolean}
+     * @memberof RecognitionConfig
+     */
+    'enabled': boolean;
+    /**
+     * 
+     * @type {number}
+     * @memberof RecognitionConfig
+     */
+    'maxDistance': number;
+    /**
+     * 
+     * @type {number}
+     * @memberof RecognitionConfig
+     */
+    'minScore': number;
+    /**
+     * 
+     * @type {string}
+     * @memberof RecognitionConfig
+     */
+    'modelName': string;
+    /**
+     * 
+     * @type {ModelType}
+     * @memberof RecognitionConfig
+     */
+    'modelType'?: ModelType;
+}
+
+
 /**
  * 
  * @export
@@ -2803,28 +2937,28 @@ export interface SystemConfigJobDto {
 export interface SystemConfigMachineLearningDto {
     /**
      * 
-     * @type {boolean}
+     * @type {ClassificationConfig}
      * @memberof SystemConfigMachineLearningDto
      */
-    'clipEncodeEnabled': boolean;
+    'classification': ClassificationConfig;
     /**
      * 
-     * @type {boolean}
+     * @type {CLIPConfig}
      * @memberof SystemConfigMachineLearningDto
      */
-    'enabled': boolean;
+    'clip': CLIPConfig;
     /**
      * 
      * @type {boolean}
      * @memberof SystemConfigMachineLearningDto
      */
-    'facialRecognitionEnabled': boolean;
+    'enabled': boolean;
     /**
      * 
-     * @type {boolean}
+     * @type {RecognitionConfig}
      * @memberof SystemConfigMachineLearningDto
      */
-    'tagImageEnabled': boolean;
+    'facialRecognition': RecognitionConfig;
     /**
      * 
      * @type {string}

machine-learning/app/config.py

@@ -8,17 +8,11 @@ from .schemas import ModelType
 
 class Settings(BaseSettings):
     cache_folder: str = "/cache"
-    classification_model: str = "microsoft/resnet-50"
-    clip_image_model: str = "ViT-B-32::openai"
-    clip_text_model: str = "ViT-B-32::openai"
-    facial_recognition_model: str = "buffalo_l"
-    min_tag_score: float = 0.9
     eager_startup: bool = False
     model_ttl: int = 0
     host: str = "0.0.0.0"
     port: int = 3003
     workers: int = 1
-    min_face_score: float = 0.7
     test_full: bool = False
     request_threads: int = os.cpu_count() or 4
     model_inter_op_threads: int = 1

machine-learning/app/main.py

@@ -1,29 +1,26 @@
 import asyncio
 import os
 from concurrent.futures import ThreadPoolExecutor
-from io import BytesIO
 from typing import Any
 
-import cv2
-import numpy as np
+import orjson
 import uvicorn
-from fastapi import Body, Depends, FastAPI
-from PIL import Image
+from fastapi import FastAPI, Form, HTTPException, UploadFile
+from fastapi.responses import ORJSONResponse
+from starlette.formparsers import MultiPartParser
 
 from app.models.base import InferenceModel
 
 from .config import settings
 from .models.cache import ModelCache
 from .schemas import (
-    EmbeddingResponse,
-    FaceResponse,
     MessageResponse,
     ModelType,
-    TagResponse,
-    TextModelRequest,
     TextResponse,
 )
 
+MultiPartParser.max_file_size = 2**24  # spools to disk if payload is 16 MiB or larger
+
 app = FastAPI()
 
 
@@ -33,37 +30,9 @@ def init_state() -> None:
     app.state.thread_pool = ThreadPoolExecutor(settings.request_threads)
 
 
-async def load_models() -> None:
-    models: list[tuple[str, ModelType, dict[str, Any]]] = [
-        (settings.classification_model, ModelType.IMAGE_CLASSIFICATION, {}),
-        (settings.clip_image_model, ModelType.CLIP, {"mode": "vision"}),
-        (settings.clip_text_model, ModelType.CLIP, {"mode": "text"}),
-        (settings.facial_recognition_model, ModelType.FACIAL_RECOGNITION, {}),
-    ]
-
-    # Get all models
-    for model_name, model_type, model_kwargs in models:
-        await app.state.model_cache.get(model_name, model_type, eager=settings.eager_startup, **model_kwargs)
-
-
 @app.on_event("startup")
 async def startup_event() -> None:
     init_state()
-    await load_models()
-
-
-@app.on_event("shutdown")
-async def shutdown_event() -> None:
-    app.state.thread_pool.shutdown()
-
-
-def dep_pil_image(byte_image: bytes = Body(...)) -> Image.Image:
-    return Image.open(BytesIO(byte_image))
-
-
-def dep_cv_image(byte_image: bytes = Body(...)) -> np.ndarray[int, np.dtype[Any]]:
-    byte_image_np = np.frombuffer(byte_image, np.uint8)
-    return cv2.imdecode(byte_image_np, cv2.IMREAD_COLOR)
 
 
 @app.get("/", response_model=MessageResponse)
@@ -76,57 +45,27 @@ def ping() -> str:
     return "pong"
 
 
-@app.post(
-    "/image-classifier/tag-image",
-    response_model=TagResponse,
-    status_code=200,
-)
-async def image_classification(
-    image: Image.Image = Depends(dep_pil_image),
-) -> list[str]:
-    model = await app.state.model_cache.get(settings.classification_model, ModelType.IMAGE_CLASSIFICATION)
-    labels = await predict(model, image)
-    return labels
-
-
-@app.post(
-    "/sentence-transformer/encode-image",
-    response_model=EmbeddingResponse,
-    status_code=200,
-)
-async def clip_encode_image(
-    image: Image.Image = Depends(dep_pil_image),
-) -> list[float]:
-    model = await app.state.model_cache.get(settings.clip_image_model, ModelType.CLIP, mode="vision")
-    embedding = await predict(model, image)
-    return embedding
-
-
-@app.post(
-    "/sentence-transformer/encode-text",
-    response_model=EmbeddingResponse,
-    status_code=200,
-)
-async def clip_encode_text(payload: TextModelRequest) -> list[float]:
-    model = await app.state.model_cache.get(settings.clip_text_model, ModelType.CLIP, mode="text")
-    embedding = await predict(model, payload.text)
-    return embedding
-
+@app.post("/predict")
+async def predict(
+    model_name: str = Form(alias="modelName"),
+    model_type: ModelType = Form(alias="modelType"),
+    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()
+    elif text is not None:
+        inputs = text
+    else:
+        raise HTTPException(400, "Either image or text must be provided")
 
-@app.post(
-    "/facial-recognition/detect-faces",
-    response_model=FaceResponse,
-    status_code=200,
-)
-async def facial_recognition(
-    image: cv2.Mat = Depends(dep_cv_image),
-) -> list[dict[str, Any]]:
-    model = await app.state.model_cache.get(settings.facial_recognition_model, ModelType.FACIAL_RECOGNITION)
-    faces = await predict(model, image)
-    return faces
+    model: InferenceModel = await app.state.model_cache.get(model_name, model_type, **orjson.loads(options))
+    outputs = await run(model, inputs)
+    return ORJSONResponse(outputs)
 
 
-async def predict(model: InferenceModel, inputs: Any) -> Any:
+async def run(model: InferenceModel, inputs: Any) -> Any:
     return await asyncio.get_running_loop().run_in_executor(app.state.thread_pool, model.predict, inputs)
 
 

machine-learning/app/models/base.py

@@ -60,16 +60,21 @@ class InferenceModel(ABC):
         self._load(**model_kwargs)
         self._loaded = True
 
-    def predict(self, inputs: Any) -> Any:
+    def predict(self, inputs: Any, **model_kwargs: Any) -> Any:
         if not self._loaded:
             print(f"Loading {self.model_type.value.replace('_', ' ')} model...")
             self.load()
+        if model_kwargs:
+            self.configure(**model_kwargs)
         return self._predict(inputs)
 
     @abstractmethod
     def _predict(self, inputs: Any) -> Any:
         ...
 
+    def configure(self, **model_kwargs: Any) -> None:
+        pass
+
     @abstractmethod
     def _download(self, **model_kwargs: Any) -> None:
         ...

machine-learning/app/models/clip.py

@@ -1,5 +1,6 @@
 import os
 import zipfile
+from io import BytesIO
 from typing import Any, Literal
 
 import onnxruntime as ort
@@ -8,7 +9,7 @@ from clip_server.model.clip import BICUBIC, _convert_image_to_rgb
 from clip_server.model.clip_onnx import _MODELS, _S3_BUCKET_V2, CLIPOnnxModel, download_model
 from clip_server.model.pretrained_models import _VISUAL_MODEL_IMAGE_SIZE
 from clip_server.model.tokenization import Tokenizer
-from PIL.Image import Image
+from PIL import Image
 from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
 
 from ..schemas import ModelType
@@ -74,9 +75,12 @@ class CLIPEncoder(InferenceModel):
             image_size = _VISUAL_MODEL_IMAGE_SIZE[CLIPOnnxModel.get_model_name(self.model_name)]
             self.transform = _transform_pil_image(image_size)
 
-    def _predict(self, image_or_text: Image | str) -> list[float]:
+    def _predict(self, image_or_text: Image.Image | str) -> list[float]:
+        if isinstance(image_or_text, bytes):
+            image_or_text = Image.open(BytesIO(image_or_text))
+
         match image_or_text:
-            case Image():
+            case Image.Image():
                 if self.mode == "text":
                     raise TypeError("Cannot encode image as text-only model")
                 pixel_values = self.transform(image_or_text)

machine-learning/app/models/facial_recognition.py

@@ -9,7 +9,6 @@ from insightface.model_zoo import ArcFaceONNX, RetinaFace
 from insightface.utils.face_align import norm_crop
 from insightface.utils.storage import BASE_REPO_URL, download_file
 
-from ..config import settings
 from ..schemas import ModelType
 from .base import InferenceModel
 
@@ -20,7 +19,7 @@ class FaceRecognizer(InferenceModel):
     def __init__(
         self,
         model_name: str,
-        min_score: float = settings.min_face_score,
+        min_score: float = 0.7,
         cache_dir: Path | str | None = None,
         **model_kwargs: Any,
     ) -> None:
@@ -69,11 +68,13 @@ class FaceRecognizer(InferenceModel):
         )
         self.rec_model.prepare(ctx_id=0)
 
-    def _predict(self, image: cv2.Mat) -> list[dict[str, Any]]:
+    def _predict(self, image: np.ndarray[int, np.dtype[Any]] | bytes) -> list[dict[str, Any]]:
+        if isinstance(image, bytes):
+            image = cv2.imdecode(np.frombuffer(image, np.uint8), cv2.IMREAD_COLOR)
         bboxes, kpss = self.det_model.detect(image)
         if bboxes.size == 0:
             return []
-        assert isinstance(kpss, np.ndarray)
+        assert isinstance(image, np.ndarray) and isinstance(kpss, np.ndarray)
 
         scores = bboxes[:, 4].tolist()
         bboxes = bboxes[:, :4].round().tolist()
@@ -102,3 +103,6 @@ class FaceRecognizer(InferenceModel):
     @property
     def cached(self) -> bool:
         return self.cache_dir.is_dir() and any(self.cache_dir.glob("*.onnx"))
+
+    def configure(self, **model_kwargs: Any) -> None:
+        self.det_model.det_thresh = model_kwargs.get("min_score", self.det_model.det_thresh)

machine-learning/app/models/image_classification.py

@@ -1,13 +1,13 @@
+from io import BytesIO
 from pathlib import Path
 from typing import Any
 
 from huggingface_hub import snapshot_download
 from optimum.onnxruntime import ORTModelForImageClassification
 from optimum.pipelines import pipeline
-from PIL.Image import Image
+from PIL import Image
 from transformers import AutoImageProcessor
 
-from ..config import settings
 from ..schemas import ModelType
 from .base import InferenceModel
 
@@ -18,7 +18,7 @@ class ImageClassifier(InferenceModel):
     def __init__(
         self,
         model_name: str,
-        min_score: float = settings.min_tag_score,
+        min_score: float = 0.9,
         cache_dir: Path | str | None = None,
         **model_kwargs: Any,
     ) -> None:
@@ -56,8 +56,13 @@ class ImageClassifier(InferenceModel):
                 feature_extractor=processor,
             )
 
-    def _predict(self, image: Image) -> list[str]:
+    def _predict(self, image: Image.Image | bytes) -> list[str]:
+        if isinstance(image, bytes):
+            image = Image.open(BytesIO(image))
         predictions: list[dict[str, Any]] = self.model(image)  # type: ignore
         tags = [tag for pred in predictions for tag in pred["label"].split(", ") if pred["score"] >= self.min_score]
 
         return tags
+
+    def configure(self, **model_kwargs: Any) -> None:
+        self.min_score = model_kwargs.get("min_score", self.min_score)

machine-learning/app/schemas.py

@@ -1,4 +1,4 @@
-from enum import Enum
+from enum import StrEnum
 
 from pydantic import BaseModel
 
@@ -20,18 +20,6 @@ class MessageResponse(BaseModel):
     message: str
 
 
-class TagResponse(BaseModel):
-    __root__: list[str]
-
-
-class Embedding(BaseModel):
-    __root__: list[float]
-
-
-class EmbeddingResponse(BaseModel):
-    __root__: Embedding
-
-
 class BoundingBox(BaseModel):
     x1: int
     y1: int
@@ -39,23 +27,7 @@ class BoundingBox(BaseModel):
     y2: int
 
 
-class Face(BaseModel):
-    image_width: int
-    image_height: int
-    bounding_box: BoundingBox
-    score: float
-    embedding: Embedding
-
-    class Config:
-        alias_generator = to_lower_camel
-        allow_population_by_field_name = True
-
-
-class FaceResponse(BaseModel):
-    __root__: list[Face]
-
-
-class ModelType(Enum):
+class ModelType(StrEnum):
     IMAGE_CLASSIFICATION = "image-classification"
     CLIP = "clip"
     FACIAL_RECOGNITION = "facial-recognition"

machine-learning/poetry.lock

@@ -720,69 +720,69 @@ files = [
 
 [[package]]
 name = "cython"
-version = "3.0.0"
+version = "3.0.2"
 description = "The Cython compiler for writing C extensions in the Python language."
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
-    {file = "Cython-3.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7c7d728e1a49ad01d41181e3a9ea80b8d14e825f4679e4dd837cbf7bca7998a5"},
-    {file = "Cython-3.0.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:626a4a6ef4b7ced87c348ea805488e4bd39dad9d0b39659aa9e1040b62bbfedf"},
-    {file = "Cython-3.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:33c900d1ca9f622b969ac7d8fc44bdae140a4a6c7d8819413b51f3ccd0586a09"},
-    {file = "Cython-3.0.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a65bc50dc1bc2faeafd9425defbdef6a468974f5c4192497ff7f14adccfdcd32"},
-    {file = "Cython-3.0.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:3b71b399b10b038b056ad12dce1e317a8aa7a96e99de7e4fa2fa5d1c9415cfb9"},
-    {file = "Cython-3.0.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:f42f304c097cc53e9eb5f1a1d150380353d5018a3191f1b77f0de353c762181e"},
-    {file = "Cython-3.0.0-cp310-cp310-win32.whl", hash = "sha256:3e234e2549e808d9259fdb23ebcfd145be30c638c65118326ec33a8d29248dc2"},
-    {file = "Cython-3.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:829c8333195100448a23863cf64a07e1334fae6a275aefe871458937911531b6"},
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 [[package]]
@@ -889,13 +889,13 @@ testing = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "diff-cover (>=7.5)", "p
 
 [[package]]
 name = "flask"
-version = "2.3.2"
+version = "2.3.3"
 description = "A simple framework for building complex web applications."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -903,7 +903,7 @@ blinker = ">=1.6.2"
 click = ">=8.1.3"
 itsdangerous = ">=2.1.2"
 Jinja2 = ">=3.1.2"
-Werkzeug = ">=2.3.3"
+Werkzeug = ">=2.3.7"
 
 [package.extras]
 async = ["asgiref (>=3.2)"]
@@ -1185,101 +1185,119 @@ test = ["cffi (>=1.12.2)", "coverage (>=5.0)", "dnspython (>=1.16.0,<2.0)", "idn
 
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 ]
 
 [package.dependencies]
@@ -2442,13 +2496,13 @@ numpy = [
 
 [[package]]
 name = "optimum"
-version = "1.11.2"
+version = "1.12.0"
 description = "Optimum Library is an extension of the Hugging Face Transformers library, providing a framework to integrate third-party libraries from Hardware Partners and interface with their specific functionality."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -2468,7 +2522,7 @@ diffusers = ["diffusers"]
 doc-build = ["accelerate"]
 exporters = ["onnx", "onnxruntime", "timm"]
 exporters-gpu = ["onnx", "onnxruntime-gpu", "timm"]
-exporters-tf = ["h5py", "numpy (<1.24.0)", "onnx", "onnxruntime", "tensorflow (>=2.4)", "tf2onnx", "timm"]
+exporters-tf = ["h5py", "numpy (<1.24.0)", "onnx", "onnxruntime", "tensorflow (>=2.4,<=2.12.1)", "tf2onnx", "timm"]
 furiosa = ["optimum-furiosa"]
 graphcore = ["optimum-graphcore"]
 habana = ["optimum-habana"]
@@ -2483,6 +2537,75 @@ openvino = ["optimum-intel[openvino] (>=1.10.1)"]
 quality = ["black (>=23.1,<24.0)", "ruff (>=0.0.241,<=0.0.259)"]
 tests = ["Pillow", "diffusers (>=0.17.0)", "einops", "invisible-watermark", "parameterized", "pytest", "pytest-xdist", "requests", "sacremoses", "torchaudio", "torchvision"]
 
+[[package]]
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+version = "3.9.5"
+description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
+optional = false
+python-versions = ">=3.7"
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+
 [[package]]
 name = "packaging"
 version = "23.1"
@@ -2667,13 +2790,13 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-co
 
 [[package]]
 name = "pluggy"
-version = "1.2.0"
+version = "1.3.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -2755,36 +2878,40 @@ test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
 
 [[package]]
 name = "pyarrow"
-version = "12.0.1"
+version = "13.0.0"
 description = "Python library for Apache Arrow"
 optional = false
-python-versions = ">=3.7"
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 [package.dependencies]
@@ -2993,6 +3120,20 @@ files = [
 [package.extras]
 cli = ["click (>=5.0)"]
 
+[[package]]
+name = "python-multipart"
+version = "0.0.6"
+description = "A streaming multipart parser for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
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+
+[package.extras]
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+
 [[package]]
 name = "pytz"
 version = "2023.3"
@@ -3736,13 +3877,13 @@ files = [
 
 [[package]]
 name = "tifffile"
-version = "2023.8.12"
+version = "2023.8.25"
 description = "Read and write TIFF files"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -3985,18 +4126,18 @@ telegram = ["requests"]
 
 [[package]]
 name = "transformers"
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 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
 python-versions = ">=3.8.0"
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 [package.dependencies]
 filelock = "*"
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 numpy = ">=1.17"
 packaging = ">=20.0"
 protobuf = {version = "*", optional = true, markers = "extra == \"sentencepiece\""}
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 [package.extras]
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 dev-torch = ["GitPython (<3.1.19)", "Pillow (<10.0.0)", "accelerate (>=0.20.3)", "beautifulsoup4", "black (>=23.1,<24.0)", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pytest (>=7.2.0)", "pytest-timeout", "pytest-xdist", "ray[tune]", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (>=0.0.241,<=0.0.259)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "timeout-decorator", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
-docs = ["Pillow (<10.0.0)", "accelerate (>=0.20.3)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "hf-doc-builder", "jax (>=0.2.8,!=0.3.2,<=0.4.13)", "jaxlib (>=0.1.65,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune]", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision"]
+docs = ["Pillow (<10.0.0)", "accelerate (>=0.20.3)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "hf-doc-builder", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune]", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.14)", "tensorflow-text (<2.14)", "tf2onnx", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "torchaudio", "torchvision"]
 docs-specific = ["hf-doc-builder"]
 fairscale = ["fairscale (>0.3)"]
-flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.2.8,!=0.3.2,<=0.4.13)", "jaxlib (>=0.1.65,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)"]
+flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)"]
 flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 ftfy = ["ftfy"]
 integrations = ["optuna", "ray[tune]", "sigopt"]
@@ -4050,7 +4191,7 @@ tokenizers = ["tokenizers (>=0.11.1,!=0.11.3,<0.14)"]
 torch = ["accelerate (>=0.20.3)", "torch (>=1.9,!=1.12.0)"]
 torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
 torch-vision = ["Pillow (<10.0.0)", "torchvision"]
-torchhub = ["filelock", "huggingface-hub (>=0.14.1,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "tqdm (>=4.27)"]
+torchhub = ["filelock", "huggingface-hub (>=0.15.1,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.9,!=1.12.0)", "tqdm (>=4.27)"]
 video = ["av (==9.2.0)", "decord (==0.6.0)"]
 vision = ["Pillow (<10.0.0)"]
 
@@ -4164,33 +4305,33 @@ test = ["Cython (>=0.29.32,<0.30.0)", "aiohttp", "flake8 (>=3.9.2,<3.10.0)", "my
 
 [[package]]
 name = "watchfiles"
-version = "0.19.0"
+version = "0.20.0"
 description = "Simple, modern and high performance file watching and code reload in python."
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "watchfiles-0.19.0-cp37-abi3-macosx_11_0_arm64.whl", hash = "sha256:b6577b8c6c8701ba8642ea9335a129836347894b666dd1ec2226830e263909d3"},
-    {file = "watchfiles-0.19.0-cp37-abi3-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:18b28f6ad871b82df9542ff958d0c86bb0d8310bb09eb8e87d97318a3b5273af"},
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+    {file = "watchfiles-0.20.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87d9e1f75c4f86c93d73b5bd1ebe667558357548f11b4f8af4e0e272f79413ce"},
+    {file = "watchfiles-0.20.0.tar.gz", hash = "sha256:728575b6b94c90dd531514677201e8851708e6e4b5fe7028ac506a200b622019"},
 ]
 
 [package.dependencies]
@@ -4552,4 +4693,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "1a8981686295b3de58b41192c608a69a2c05983c47f93451c8a6ed50304b7cb3"
+content-hash = "6d200d3ea1ccf9fb89f44043e3e0845e70f19aac374b96227559375f44508dc5"

machine-learning/pyproject.toml

@@ -30,6 +30,9 @@ rich = "^13.4.2"
 ftfy = "^6.1.1"
 setuptools = "^68.0.0"
 open-clip-torch = "^2.20.0"
+python-multipart = "^0.0.6"
+orjson = "^3.9.5"
+safetensors = "0.3.2"
 
 [tool.poetry.group.dev.dependencies]
 mypy = "^1.3.0"

mobile/openapi/.openapi-generator/FILES

@@ -35,11 +35,14 @@ doc/AuthDeviceResponseDto.md
 doc/AuthenticationApi.md
 doc/BulkIdResponseDto.md
 doc/BulkIdsDto.md
+doc/CLIPConfig.md
+doc/CLIPMode.md
 doc/ChangePasswordDto.md
 doc/CheckDuplicateAssetDto.md
 doc/CheckDuplicateAssetResponseDto.md
 doc/CheckExistingAssetsDto.md
 doc/CheckExistingAssetsResponseDto.md
+doc/ClassificationConfig.md
 doc/CreateAlbumDto.md
 doc/CreateProfileImageResponseDto.md
 doc/CreateTagDto.md
@@ -68,6 +71,7 @@ doc/LogoutResponseDto.md
 doc/MapMarkerResponseDto.md
 doc/MemoryLaneResponseDto.md
 doc/MergePersonDto.md
+doc/ModelType.md
 doc/OAuthApi.md
 doc/OAuthCallbackDto.md
 doc/OAuthConfigDto.md
@@ -80,6 +84,7 @@ doc/PersonApi.md
 doc/PersonResponseDto.md
 doc/PersonUpdateDto.md
 doc/QueueStatusDto.md
+doc/RecognitionConfig.md
 doc/SearchAlbumResponseDto.md
 doc/SearchApi.md
 doc/SearchAssetDto.md
@@ -189,6 +194,9 @@ lib/model/check_duplicate_asset_dto.dart
 lib/model/check_duplicate_asset_response_dto.dart
 lib/model/check_existing_assets_dto.dart
 lib/model/check_existing_assets_response_dto.dart
+lib/model/classification_config.dart
+lib/model/clip_config.dart
+lib/model/clip_mode.dart
 lib/model/create_album_dto.dart
 lib/model/create_profile_image_response_dto.dart
 lib/model/create_tag_dto.dart
@@ -216,6 +224,7 @@ lib/model/logout_response_dto.dart
 lib/model/map_marker_response_dto.dart
 lib/model/memory_lane_response_dto.dart
 lib/model/merge_person_dto.dart
+lib/model/model_type.dart
 lib/model/o_auth_callback_dto.dart
 lib/model/o_auth_config_dto.dart
 lib/model/o_auth_config_response_dto.dart
@@ -225,6 +234,7 @@ lib/model/people_update_item.dart
 lib/model/person_response_dto.dart
 lib/model/person_update_dto.dart
 lib/model/queue_status_dto.dart
+lib/model/recognition_config.dart
 lib/model/search_album_response_dto.dart
 lib/model/search_asset_dto.dart
 lib/model/search_asset_response_dto.dart
@@ -309,6 +319,9 @@ test/check_duplicate_asset_dto_test.dart
 test/check_duplicate_asset_response_dto_test.dart
 test/check_existing_assets_dto_test.dart
 test/check_existing_assets_response_dto_test.dart
+test/classification_config_test.dart
+test/clip_config_test.dart
+test/clip_mode_test.dart
 test/create_album_dto_test.dart
 test/create_profile_image_response_dto_test.dart
 test/create_tag_dto_test.dart
@@ -337,6 +350,7 @@ test/logout_response_dto_test.dart
 test/map_marker_response_dto_test.dart
 test/memory_lane_response_dto_test.dart
 test/merge_person_dto_test.dart
+test/model_type_test.dart
 test/o_auth_api_test.dart
 test/o_auth_callback_dto_test.dart
 test/o_auth_config_dto_test.dart
@@ -349,6 +363,7 @@ test/person_api_test.dart
 test/person_response_dto_test.dart
 test/person_update_dto_test.dart
 test/queue_status_dto_test.dart
+test/recognition_config_test.dart
 test/search_album_response_dto_test.dart
 test/search_api_test.dart
 test/search_asset_dto_test.dart

mobile/openapi/README.md

@@ -208,11 +208,14 @@ Class | Method | HTTP request | Description
  - [AuthDeviceResponseDto](doc//AuthDeviceResponseDto.md)
  - [BulkIdResponseDto](doc//BulkIdResponseDto.md)
  - [BulkIdsDto](doc//BulkIdsDto.md)
+ - [CLIPConfig](doc//CLIPConfig.md)
+ - [CLIPMode](doc//CLIPMode.md)
  - [ChangePasswordDto](doc//ChangePasswordDto.md)
  - [CheckDuplicateAssetDto](doc//CheckDuplicateAssetDto.md)
  - [CheckDuplicateAssetResponseDto](doc//CheckDuplicateAssetResponseDto.md)
  - [CheckExistingAssetsDto](doc//CheckExistingAssetsDto.md)
  - [CheckExistingAssetsResponseDto](doc//CheckExistingAssetsResponseDto.md)
+ - [ClassificationConfig](doc//ClassificationConfig.md)
  - [CreateAlbumDto](doc//CreateAlbumDto.md)
  - [CreateProfileImageResponseDto](doc//CreateProfileImageResponseDto.md)
  - [CreateTagDto](doc//CreateTagDto.md)
@@ -240,6 +243,7 @@ Class | Method | HTTP request | Description
  - [MapMarkerResponseDto](doc//MapMarkerResponseDto.md)
  - [MemoryLaneResponseDto](doc//MemoryLaneResponseDto.md)
  - [MergePersonDto](doc//MergePersonDto.md)
+ - [ModelType](doc//ModelType.md)
  - [OAuthCallbackDto](doc//OAuthCallbackDto.md)
  - [OAuthConfigDto](doc//OAuthConfigDto.md)
  - [OAuthConfigResponseDto](doc//OAuthConfigResponseDto.md)
@@ -249,6 +253,7 @@ Class | Method | HTTP request | Description
  - [PersonResponseDto](doc//PersonResponseDto.md)
  - [PersonUpdateDto](doc//PersonUpdateDto.md)
  - [QueueStatusDto](doc//QueueStatusDto.md)
+ - [RecognitionConfig](doc//RecognitionConfig.md)
  - [SearchAlbumResponseDto](doc//SearchAlbumResponseDto.md)
  - [SearchAssetDto](doc//SearchAssetDto.md)
  - [SearchAssetResponseDto](doc//SearchAssetResponseDto.md)

mobile/openapi/doc/CLIPConfig.md

@@ -0,0 +1,18 @@
+# openapi.model.CLIPConfig
+
+## Load the model package
+```dart
+import 'package:openapi/api.dart';
+```
+
+## Properties
+Name | Type | Description | Notes
+------------ | ------------- | ------------- | -------------
+**enabled** | **bool** |  | 
+**mode** | [**CLIPMode**](CLIPMode.md) |  | [optional] 
+**modelName** | **String** |  | 
+**modelType** | [**ModelType**](ModelType.md) |  | [optional] 
+
+[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
+
+

mobile/openapi/doc/CLIPMode.md

@@ -0,0 +1,14 @@
+# openapi.model.CLIPMode
+
+## Load the model package
+```dart
+import 'package:openapi/api.dart';
+```
+
+## Properties
+Name | Type | Description | Notes
+------------ | ------------- | ------------- | -------------
+
+[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
+
+

mobile/openapi/doc/ClassificationConfig.md

@@ -0,0 +1,18 @@
+# openapi.model.ClassificationConfig
+
+## Load the model package
+```dart
+import 'package:openapi/api.dart';
+```
+
+## Properties
+Name | Type | Description | Notes
+------------ | ------------- | ------------- | -------------
+**enabled** | **bool** |  | 
+**minScore** | **int** |  | 
+**modelName** | **String** |  | 
+**modelType** | [**ModelType**](ModelType.md) |  | [optional] 
+
+[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
+
+

mobile/openapi/doc/ModelType.md

@@ -0,0 +1,14 @@
+# openapi.model.ModelType
+
+## Load the model package
+```dart
+import 'package:openapi/api.dart';
+```
+
+## Properties
+Name | Type | Description | Notes
+------------ | ------------- | ------------- | -------------
+
+[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
+
+

mobile/openapi/doc/RecognitionConfig.md

@@ -0,0 +1,19 @@
+# openapi.model.RecognitionConfig
+
+## Load the model package
+```dart
+import 'package:openapi/api.dart';
+```
+
+## Properties
+Name | Type | Description | Notes
+------------ | ------------- | ------------- | -------------
+**enabled** | **bool** |  | 
+**maxDistance** | **int** |  | 
+**minScore** | **int** |  | 
+**modelName** | **String** |  | 
+**modelType** | [**ModelType**](ModelType.md) |  | [optional] 
+
+[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
+
+

mobile/openapi/doc/SystemConfigMachineLearningDto.md

@@ -8,10 +8,10 @@ import 'package:openapi/api.dart';
 ## Properties
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
-**clipEncodeEnabled** | **bool** |  | 
+**classification** | [**ClassificationConfig**](ClassificationConfig.md) |  | 
+**clip** | [**CLIPConfig**](CLIPConfig.md) |  | 
 **enabled** | **bool** |  | 
-**facialRecognitionEnabled** | **bool** |  | 
-**tagImageEnabled** | **bool** |  | 
+**facialRecognition** | [**RecognitionConfig**](RecognitionConfig.md) |  | 
 **url** | **String** |  | 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)

mobile/openapi/lib/api.dart

@@ -71,11 +71,14 @@ part 'model/audit_deletes_response_dto.dart';
 part 'model/auth_device_response_dto.dart';
 part 'model/bulk_id_response_dto.dart';
 part 'model/bulk_ids_dto.dart';
+part 'model/clip_config.dart';
+part 'model/clip_mode.dart';
 part 'model/change_password_dto.dart';
 part 'model/check_duplicate_asset_dto.dart';
 part 'model/check_duplicate_asset_response_dto.dart';
 part 'model/check_existing_assets_dto.dart';
 part 'model/check_existing_assets_response_dto.dart';
+part 'model/classification_config.dart';
 part 'model/create_album_dto.dart';
 part 'model/create_profile_image_response_dto.dart';
 part 'model/create_tag_dto.dart';
@@ -103,6 +106,7 @@ part 'model/logout_response_dto.dart';
 part 'model/map_marker_response_dto.dart';
 part 'model/memory_lane_response_dto.dart';
 part 'model/merge_person_dto.dart';
+part 'model/model_type.dart';
 part 'model/o_auth_callback_dto.dart';
 part 'model/o_auth_config_dto.dart';
 part 'model/o_auth_config_response_dto.dart';
@@ -112,6 +116,7 @@ part 'model/people_update_item.dart';
 part 'model/person_response_dto.dart';
 part 'model/person_update_dto.dart';
 part 'model/queue_status_dto.dart';
+part 'model/recognition_config.dart';
 part 'model/search_album_response_dto.dart';
 part 'model/search_asset_dto.dart';
 part 'model/search_asset_response_dto.dart';

mobile/openapi/lib/api_client.dart

@@ -235,6 +235,10 @@ class ApiClient {
           return BulkIdResponseDto.fromJson(value);
         case 'BulkIdsDto':
           return BulkIdsDto.fromJson(value);
+        case 'CLIPConfig':
+          return CLIPConfig.fromJson(value);
+        case 'CLIPMode':
+          return CLIPModeTypeTransformer().decode(value);
         case 'ChangePasswordDto':
           return ChangePasswordDto.fromJson(value);
         case 'CheckDuplicateAssetDto':
@@ -245,6 +249,8 @@ class ApiClient {
           return CheckExistingAssetsDto.fromJson(value);
         case 'CheckExistingAssetsResponseDto':
           return CheckExistingAssetsResponseDto.fromJson(value);
+        case 'ClassificationConfig':
+          return ClassificationConfig.fromJson(value);
         case 'CreateAlbumDto':
           return CreateAlbumDto.fromJson(value);
         case 'CreateProfileImageResponseDto':
@@ -299,6 +305,8 @@ class ApiClient {
           return MemoryLaneResponseDto.fromJson(value);
         case 'MergePersonDto':
           return MergePersonDto.fromJson(value);
+        case 'ModelType':
+          return ModelTypeTypeTransformer().decode(value);
         case 'OAuthCallbackDto':
           return OAuthCallbackDto.fromJson(value);
         case 'OAuthConfigDto':
@@ -317,6 +325,8 @@ class ApiClient {
           return PersonUpdateDto.fromJson(value);
         case 'QueueStatusDto':
           return QueueStatusDto.fromJson(value);
+        case 'RecognitionConfig':
+          return RecognitionConfig.fromJson(value);
         case 'SearchAlbumResponseDto':
           return SearchAlbumResponseDto.fromJson(value);
         case 'SearchAssetDto':

mobile/openapi/lib/api_helper.dart

@@ -64,6 +64,9 @@ String parameterToString(dynamic value) {
   if (value is AudioCodec) {
     return AudioCodecTypeTransformer().encode(value).toString();
   }
+  if (value is CLIPMode) {
+    return CLIPModeTypeTransformer().encode(value).toString();
+  }
   if (value is DeleteAssetStatus) {
     return DeleteAssetStatusTypeTransformer().encode(value).toString();
   }
@@ -76,6 +79,9 @@ String parameterToString(dynamic value) {
   if (value is JobName) {
     return JobNameTypeTransformer().encode(value).toString();
   }
+  if (value is ModelType) {
+    return ModelTypeTypeTransformer().encode(value).toString();
+  }
   if (value is SharedLinkType) {
     return SharedLinkTypeTypeTransformer().encode(value).toString();
   }

mobile/openapi/lib/model/classification_config.dart

@@ -0,0 +1,131 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+part of openapi.api;
+
+class ClassificationConfig {
+  /// Returns a new [ClassificationConfig] instance.
+  ClassificationConfig({
+    required this.enabled,
+    required this.minScore,
+    required this.modelName,
+    this.modelType,
+  });
+
+  bool enabled;
+
+  int minScore;
+
+  String modelName;
+
+  ///
+  /// Please note: This property should have been non-nullable! Since the specification file
+  /// does not include a default value (using the "default:" property), however, the generated
+  /// source code must fall back to having a nullable type.
+  /// Consider adding a "default:" property in the specification file to hide this note.
+  ///
+  ModelType? modelType;
+
+  @override
+  bool operator ==(Object other) => identical(this, other) || other is ClassificationConfig &&
+     other.enabled == enabled &&
+     other.minScore == minScore &&
+     other.modelName == modelName &&
+     other.modelType == modelType;
+
+  @override
+  int get hashCode =>
+    // ignore: unnecessary_parenthesis
+    (enabled.hashCode) +
+    (minScore.hashCode) +
+    (modelName.hashCode) +
+    (modelType == null ? 0 : modelType!.hashCode);
+
+  @override
+  String toString() => 'ClassificationConfig[enabled=$enabled, minScore=$minScore, modelName=$modelName, modelType=$modelType]';
+
+  Map<String, dynamic> toJson() {
+    final json = <String, dynamic>{};
+      json[r'enabled'] = this.enabled;
+      json[r'minScore'] = this.minScore;
+      json[r'modelName'] = this.modelName;
+    if (this.modelType != null) {
+      json[r'modelType'] = this.modelType;
+    } else {
+    //  json[r'modelType'] = null;
+    }
+    return json;
+  }
+
+  /// Returns a new [ClassificationConfig] instance and imports its values from
+  /// [value] if it's a [Map], null otherwise.
+  // ignore: prefer_constructors_over_static_methods
+  static ClassificationConfig? fromJson(dynamic value) {
+    if (value is Map) {
+      final json = value.cast<String, dynamic>();
+
+      return ClassificationConfig(
+        enabled: mapValueOfType<bool>(json, r'enabled')!,
+        minScore: mapValueOfType<int>(json, r'minScore')!,
+        modelName: mapValueOfType<String>(json, r'modelName')!,
+        modelType: ModelType.fromJson(json[r'modelType']),
+      );
+    }
+    return null;
+  }
+
+  static List<ClassificationConfig> listFromJson(dynamic json, {bool growable = false,}) {
+    final result = <ClassificationConfig>[];
+    if (json is List && json.isNotEmpty) {
+      for (final row in json) {
+        final value = ClassificationConfig.fromJson(row);
+        if (value != null) {
+          result.add(value);
+        }
+      }
+    }
+    return result.toList(growable: growable);
+  }
+
+  static Map<String, ClassificationConfig> mapFromJson(dynamic json) {
+    final map = <String, ClassificationConfig>{};
+    if (json is Map && json.isNotEmpty) {
+      json = json.cast<String, dynamic>(); // ignore: parameter_assignments
+      for (final entry in json.entries) {
+        final value = ClassificationConfig.fromJson(entry.value);
+        if (value != null) {
+          map[entry.key] = value;
+        }
+      }
+    }
+    return map;
+  }
+
+  // maps a json object with a list of ClassificationConfig-objects as value to a dart map
+  static Map<String, List<ClassificationConfig>> mapListFromJson(dynamic json, {bool growable = false,}) {
+    final map = <String, List<ClassificationConfig>>{};
+    if (json is Map && json.isNotEmpty) {
+      // ignore: parameter_assignments
+      json = json.cast<String, dynamic>();
+      for (final entry in json.entries) {
+        map[entry.key] = ClassificationConfig.listFromJson(entry.value, growable: growable,);
+      }
+    }
+    return map;
+  }
+
+  /// The list of required keys that must be present in a JSON.
+  static const requiredKeys = <String>{
+    'enabled',
+    'minScore',
+    'modelName',
+  };
+}
+

mobile/openapi/lib/model/clip_config.dart

@@ -0,0 +1,140 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+part of openapi.api;
+
+class CLIPConfig {
+  /// Returns a new [CLIPConfig] instance.
+  CLIPConfig({
+    required this.enabled,
+    this.mode,
+    required this.modelName,
+    this.modelType,
+  });
+
+  bool enabled;
+
+  ///
+  /// Please note: This property should have been non-nullable! Since the specification file
+  /// does not include a default value (using the "default:" property), however, the generated
+  /// source code must fall back to having a nullable type.
+  /// Consider adding a "default:" property in the specification file to hide this note.
+  ///
+  CLIPMode? mode;
+
+  String modelName;
+
+  ///
+  /// Please note: This property should have been non-nullable! Since the specification file
+  /// does not include a default value (using the "default:" property), however, the generated
+  /// source code must fall back to having a nullable type.
+  /// Consider adding a "default:" property in the specification file to hide this note.
+  ///
+  ModelType? modelType;
+
+  @override
+  bool operator ==(Object other) => identical(this, other) || other is CLIPConfig &&
+     other.enabled == enabled &&
+     other.mode == mode &&
+     other.modelName == modelName &&
+     other.modelType == modelType;
+
+  @override
+  int get hashCode =>
+    // ignore: unnecessary_parenthesis
+    (enabled.hashCode) +
+    (mode == null ? 0 : mode!.hashCode) +
+    (modelName.hashCode) +
+    (modelType == null ? 0 : modelType!.hashCode);
+
+  @override
+  String toString() => 'CLIPConfig[enabled=$enabled, mode=$mode, modelName=$modelName, modelType=$modelType]';
+
+  Map<String, dynamic> toJson() {
+    final json = <String, dynamic>{};
+      json[r'enabled'] = this.enabled;
+    if (this.mode != null) {
+      json[r'mode'] = this.mode;
+    } else {
+    //  json[r'mode'] = null;
+    }
+      json[r'modelName'] = this.modelName;
+    if (this.modelType != null) {
+      json[r'modelType'] = this.modelType;
+    } else {
+    //  json[r'modelType'] = null;
+    }
+    return json;
+  }
+
+  /// Returns a new [CLIPConfig] instance and imports its values from
+  /// [value] if it's a [Map], null otherwise.
+  // ignore: prefer_constructors_over_static_methods
+  static CLIPConfig? fromJson(dynamic value) {
+    if (value is Map) {
+      final json = value.cast<String, dynamic>();
+
+      return CLIPConfig(
+        enabled: mapValueOfType<bool>(json, r'enabled')!,
+        mode: CLIPMode.fromJson(json[r'mode']),
+        modelName: mapValueOfType<String>(json, r'modelName')!,
+        modelType: ModelType.fromJson(json[r'modelType']),
+      );
+    }
+    return null;
+  }
+
+  static List<CLIPConfig> listFromJson(dynamic json, {bool growable = false,}) {
+    final result = <CLIPConfig>[];
+    if (json is List && json.isNotEmpty) {
+      for (final row in json) {
+        final value = CLIPConfig.fromJson(row);
+        if (value != null) {
+          result.add(value);
+        }
+      }
+    }
+    return result.toList(growable: growable);
+  }
+
+  static Map<String, CLIPConfig> mapFromJson(dynamic json) {
+    final map = <String, CLIPConfig>{};
+    if (json is Map && json.isNotEmpty) {
+      json = json.cast<String, dynamic>(); // ignore: parameter_assignments
+      for (final entry in json.entries) {
+        final value = CLIPConfig.fromJson(entry.value);
+        if (value != null) {
+          map[entry.key] = value;
+        }
+      }
+    }
+    return map;
+  }
+
+  // maps a json object with a list of CLIPConfig-objects as value to a dart map
+  static Map<String, List<CLIPConfig>> mapListFromJson(dynamic json, {bool growable = false,}) {
+    final map = <String, List<CLIPConfig>>{};
+    if (json is Map && json.isNotEmpty) {
+      // ignore: parameter_assignments
+      json = json.cast<String, dynamic>();
+      for (final entry in json.entries) {
+        map[entry.key] = CLIPConfig.listFromJson(entry.value, growable: growable,);
+      }
+    }
+    return map;
+  }
+
+  /// The list of required keys that must be present in a JSON.
+  static const requiredKeys = <String>{
+    'enabled',
+    'modelName',
+  };
+}
+

mobile/openapi/lib/model/clip_mode.dart

@@ -0,0 +1,85 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+part of openapi.api;
+
+
+class CLIPMode {
+  /// Instantiate a new enum with the provided [value].
+  const CLIPMode._(this.value);
+
+  /// The underlying value of this enum member.
+  final String value;
+
+  @override
+  String toString() => value;
+
+  String toJson() => value;
+
+  static const vision = CLIPMode._(r'vision');
+  static const text = CLIPMode._(r'text');
+
+  /// List of all possible values in this [enum][CLIPMode].
+  static const values = <CLIPMode>[
+    vision,
+    text,
+  ];
+
+  static CLIPMode? fromJson(dynamic value) => CLIPModeTypeTransformer().decode(value);
+
+  static List<CLIPMode>? listFromJson(dynamic json, {bool growable = false,}) {
+    final result = <CLIPMode>[];
+    if (json is List && json.isNotEmpty) {
+      for (final row in json) {
+        final value = CLIPMode.fromJson(row);
+        if (value != null) {
+          result.add(value);
+        }
+      }
+    }
+    return result.toList(growable: growable);
+  }
+}
+
+/// Transformation class that can [encode] an instance of [CLIPMode] to String,
+/// and [decode] dynamic data back to [CLIPMode].
+class CLIPModeTypeTransformer {
+  factory CLIPModeTypeTransformer() => _instance ??= const CLIPModeTypeTransformer._();
+
+  const CLIPModeTypeTransformer._();
+
+  String encode(CLIPMode data) => data.value;
+
+  /// Decodes a [dynamic value][data] to a CLIPMode.
+  ///
+  /// If [allowNull] is true and the [dynamic value][data] cannot be decoded successfully,
+  /// then null is returned. However, if [allowNull] is false and the [dynamic value][data]
+  /// cannot be decoded successfully, then an [UnimplementedError] is thrown.
+  ///
+  /// The [allowNull] is very handy when an API changes and a new enum value is added or removed,
+  /// and users are still using an old app with the old code.
+  CLIPMode? decode(dynamic data, {bool allowNull = true}) {
+    if (data != null) {
+      switch (data) {
+        case r'vision': return CLIPMode.vision;
+        case r'text': return CLIPMode.text;
+        default:
+          if (!allowNull) {
+            throw ArgumentError('Unknown enum value to decode: $data');
+          }
+      }
+    }
+    return null;
+  }
+
+  /// Singleton [CLIPModeTypeTransformer] instance.
+  static CLIPModeTypeTransformer? _instance;
+}
+

mobile/openapi/lib/model/model_type.dart

@@ -0,0 +1,88 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+part of openapi.api;
+
+
+class ModelType {
+  /// Instantiate a new enum with the provided [value].
+  const ModelType._(this.value);
+
+  /// The underlying value of this enum member.
+  final String value;
+
+  @override
+  String toString() => value;
+
+  String toJson() => value;
+
+  static const imageClassification = ModelType._(r'image-classification');
+  static const facialRecognition = ModelType._(r'facial-recognition');
+  static const clip = ModelType._(r'clip');
+
+  /// List of all possible values in this [enum][ModelType].
+  static const values = <ModelType>[
+    imageClassification,
+    facialRecognition,
+    clip,
+  ];
+
+  static ModelType? fromJson(dynamic value) => ModelTypeTypeTransformer().decode(value);
+
+  static List<ModelType>? listFromJson(dynamic json, {bool growable = false,}) {
+    final result = <ModelType>[];
+    if (json is List && json.isNotEmpty) {
+      for (final row in json) {
+        final value = ModelType.fromJson(row);
+        if (value != null) {
+          result.add(value);
+        }
+      }
+    }
+    return result.toList(growable: growable);
+  }
+}
+
+/// Transformation class that can [encode] an instance of [ModelType] to String,
+/// and [decode] dynamic data back to [ModelType].
+class ModelTypeTypeTransformer {
+  factory ModelTypeTypeTransformer() => _instance ??= const ModelTypeTypeTransformer._();
+
+  const ModelTypeTypeTransformer._();
+
+  String encode(ModelType data) => data.value;
+
+  /// Decodes a [dynamic value][data] to a ModelType.
+  ///
+  /// If [allowNull] is true and the [dynamic value][data] cannot be decoded successfully,
+  /// then null is returned. However, if [allowNull] is false and the [dynamic value][data]
+  /// cannot be decoded successfully, then an [UnimplementedError] is thrown.
+  ///
+  /// The [allowNull] is very handy when an API changes and a new enum value is added or removed,
+  /// and users are still using an old app with the old code.
+  ModelType? decode(dynamic data, {bool allowNull = true}) {
+    if (data != null) {
+      switch (data) {
+        case r'image-classification': return ModelType.imageClassification;
+        case r'facial-recognition': return ModelType.facialRecognition;
+        case r'clip': return ModelType.clip;
+        default:
+          if (!allowNull) {
+            throw ArgumentError('Unknown enum value to decode: $data');
+          }
+      }
+    }
+    return null;
+  }
+
+  /// Singleton [ModelTypeTypeTransformer] instance.
+  static ModelTypeTypeTransformer? _instance;
+}
+

mobile/openapi/lib/model/recognition_config.dart

@@ -0,0 +1,139 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+part of openapi.api;
+
+class RecognitionConfig {
+  /// Returns a new [RecognitionConfig] instance.
+  RecognitionConfig({
+    required this.enabled,
+    required this.maxDistance,
+    required this.minScore,
+    required this.modelName,
+    this.modelType,
+  });
+
+  bool enabled;
+
+  int maxDistance;
+
+  int minScore;
+
+  String modelName;
+
+  ///
+  /// Please note: This property should have been non-nullable! Since the specification file
+  /// does not include a default value (using the "default:" property), however, the generated
+  /// source code must fall back to having a nullable type.
+  /// Consider adding a "default:" property in the specification file to hide this note.
+  ///
+  ModelType? modelType;
+
+  @override
+  bool operator ==(Object other) => identical(this, other) || other is RecognitionConfig &&
+     other.enabled == enabled &&
+     other.maxDistance == maxDistance &&
+     other.minScore == minScore &&
+     other.modelName == modelName &&
+     other.modelType == modelType;
+
+  @override
+  int get hashCode =>
+    // ignore: unnecessary_parenthesis
+    (enabled.hashCode) +
+    (maxDistance.hashCode) +
+    (minScore.hashCode) +
+    (modelName.hashCode) +
+    (modelType == null ? 0 : modelType!.hashCode);
+
+  @override
+  String toString() => 'RecognitionConfig[enabled=$enabled, maxDistance=$maxDistance, minScore=$minScore, modelName=$modelName, modelType=$modelType]';
+
+  Map<String, dynamic> toJson() {
+    final json = <String, dynamic>{};
+      json[r'enabled'] = this.enabled;
+      json[r'maxDistance'] = this.maxDistance;
+      json[r'minScore'] = this.minScore;
+      json[r'modelName'] = this.modelName;
+    if (this.modelType != null) {
+      json[r'modelType'] = this.modelType;
+    } else {
+    //  json[r'modelType'] = null;
+    }
+    return json;
+  }
+
+  /// Returns a new [RecognitionConfig] instance and imports its values from
+  /// [value] if it's a [Map], null otherwise.
+  // ignore: prefer_constructors_over_static_methods
+  static RecognitionConfig? fromJson(dynamic value) {
+    if (value is Map) {
+      final json = value.cast<String, dynamic>();
+
+      return RecognitionConfig(
+        enabled: mapValueOfType<bool>(json, r'enabled')!,
+        maxDistance: mapValueOfType<int>(json, r'maxDistance')!,
+        minScore: mapValueOfType<int>(json, r'minScore')!,
+        modelName: mapValueOfType<String>(json, r'modelName')!,
+        modelType: ModelType.fromJson(json[r'modelType']),
+      );
+    }
+    return null;
+  }
+
+  static List<RecognitionConfig> listFromJson(dynamic json, {bool growable = false,}) {
+    final result = <RecognitionConfig>[];
+    if (json is List && json.isNotEmpty) {
+      for (final row in json) {
+        final value = RecognitionConfig.fromJson(row);
+        if (value != null) {
+          result.add(value);
+        }
+      }
+    }
+    return result.toList(growable: growable);
+  }
+
+  static Map<String, RecognitionConfig> mapFromJson(dynamic json) {
+    final map = <String, RecognitionConfig>{};
+    if (json is Map && json.isNotEmpty) {
+      json = json.cast<String, dynamic>(); // ignore: parameter_assignments
+      for (final entry in json.entries) {
+        final value = RecognitionConfig.fromJson(entry.value);
+        if (value != null) {
+          map[entry.key] = value;
+        }
+      }
+    }
+    return map;
+  }
+
+  // maps a json object with a list of RecognitionConfig-objects as value to a dart map
+  static Map<String, List<RecognitionConfig>> mapListFromJson(dynamic json, {bool growable = false,}) {
+    final map = <String, List<RecognitionConfig>>{};
+    if (json is Map && json.isNotEmpty) {
+      // ignore: parameter_assignments
+      json = json.cast<String, dynamic>();
+      for (final entry in json.entries) {
+        map[entry.key] = RecognitionConfig.listFromJson(entry.value, growable: growable,);
+      }
+    }
+    return map;
+  }
+
+  /// The list of required keys that must be present in a JSON.
+  static const requiredKeys = <String>{
+    'enabled',
+    'maxDistance',
+    'minScore',
+    'modelName',
+  };
+}
+

mobile/openapi/lib/model/system_config_machine_learning_dto.dart

@@ -13,49 +13,49 @@ part of openapi.api;
 class SystemConfigMachineLearningDto {
   /// Returns a new [SystemConfigMachineLearningDto] instance.
   SystemConfigMachineLearningDto({
-    required this.clipEncodeEnabled,
+    required this.classification,
+    required this.clip,
     required this.enabled,
-    required this.facialRecognitionEnabled,
-    required this.tagImageEnabled,
+    required this.facialRecognition,
     required this.url,
   });
 
-  bool clipEncodeEnabled;
+  ClassificationConfig classification;
 
-  bool enabled;
+  CLIPConfig clip;
 
-  bool facialRecognitionEnabled;
+  bool enabled;
 
-  bool tagImageEnabled;
+  RecognitionConfig facialRecognition;
 
   String url;
 
   @override
   bool operator ==(Object other) => identical(this, other) || other is SystemConfigMachineLearningDto &&
-     other.clipEncodeEnabled == clipEncodeEnabled &&
+     other.classification == classification &&
+     other.clip == clip &&
      other.enabled == enabled &&
-     other.facialRecognitionEnabled == facialRecognitionEnabled &&
-     other.tagImageEnabled == tagImageEnabled &&
+     other.facialRecognition == facialRecognition &&
      other.url == url;
 
   @override
   int get hashCode =>
     // ignore: unnecessary_parenthesis
-    (clipEncodeEnabled.hashCode) +
+    (classification.hashCode) +
+    (clip.hashCode) +
     (enabled.hashCode) +
-    (facialRecognitionEnabled.hashCode) +
-    (tagImageEnabled.hashCode) +
+    (facialRecognition.hashCode) +
     (url.hashCode);
 
   @override
-  String toString() => 'SystemConfigMachineLearningDto[clipEncodeEnabled=$clipEncodeEnabled, enabled=$enabled, facialRecognitionEnabled=$facialRecognitionEnabled, tagImageEnabled=$tagImageEnabled, url=$url]';
+  String toString() => 'SystemConfigMachineLearningDto[classification=$classification, clip=$clip, enabled=$enabled, facialRecognition=$facialRecognition, url=$url]';
 
   Map<String, dynamic> toJson() {
     final json = <String, dynamic>{};
-      json[r'clipEncodeEnabled'] = this.clipEncodeEnabled;
+      json[r'classification'] = this.classification;
+      json[r'clip'] = this.clip;
       json[r'enabled'] = this.enabled;
-      json[r'facialRecognitionEnabled'] = this.facialRecognitionEnabled;
-      json[r'tagImageEnabled'] = this.tagImageEnabled;
+      json[r'facialRecognition'] = this.facialRecognition;
       json[r'url'] = this.url;
     return json;
   }
@@ -68,10 +68,10 @@ class SystemConfigMachineLearningDto {
       final json = value.cast<String, dynamic>();
 
       return SystemConfigMachineLearningDto(
-        clipEncodeEnabled: mapValueOfType<bool>(json, r'clipEncodeEnabled')!,
+        classification: ClassificationConfig.fromJson(json[r'classification'])!,
+        clip: CLIPConfig.fromJson(json[r'clip'])!,
         enabled: mapValueOfType<bool>(json, r'enabled')!,
-        facialRecognitionEnabled: mapValueOfType<bool>(json, r'facialRecognitionEnabled')!,
-        tagImageEnabled: mapValueOfType<bool>(json, r'tagImageEnabled')!,
+        facialRecognition: RecognitionConfig.fromJson(json[r'facialRecognition'])!,
         url: mapValueOfType<String>(json, r'url')!,
       );
     }
@@ -120,10 +120,10 @@ class SystemConfigMachineLearningDto {
 
   /// The list of required keys that must be present in a JSON.
   static const requiredKeys = <String>{
-    'clipEncodeEnabled',
+    'classification',
+    'clip',
     'enabled',
-    'facialRecognitionEnabled',
-    'tagImageEnabled',
+    'facialRecognition',
     'url',
   };
 }

mobile/openapi/test/classification_config_test.dart

@@ -0,0 +1,42 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+import 'package:openapi/api.dart';
+import 'package:test/test.dart';
+
+// tests for ClassificationConfig
+void main() {
+  // final instance = ClassificationConfig();
+
+  group('test ClassificationConfig', () {
+    // bool enabled
+    test('to test the property `enabled`', () async {
+      // TODO
+    });
+
+    // int minScore
+    test('to test the property `minScore`', () async {
+      // TODO
+    });
+
+    // String modelName
+    test('to test the property `modelName`', () async {
+      // TODO
+    });
+
+    // ModelType modelType
+    test('to test the property `modelType`', () async {
+      // TODO
+    });
+
+
+  });
+
+}

mobile/openapi/test/clip_config_test.dart

@@ -0,0 +1,42 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+import 'package:openapi/api.dart';
+import 'package:test/test.dart';
+
+// tests for CLIPConfig
+void main() {
+  // final instance = CLIPConfig();
+
+  group('test CLIPConfig', () {
+    // bool enabled
+    test('to test the property `enabled`', () async {
+      // TODO
+    });
+
+    // CLIPMode mode
+    test('to test the property `mode`', () async {
+      // TODO
+    });
+
+    // String modelName
+    test('to test the property `modelName`', () async {
+      // TODO
+    });
+
+    // ModelType modelType
+    test('to test the property `modelType`', () async {
+      // TODO
+    });
+
+
+  });
+
+}

mobile/openapi/test/clip_mode_test.dart

@@ -0,0 +1,21 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+import 'package:openapi/api.dart';
+import 'package:test/test.dart';
+
+// tests for CLIPMode
+void main() {
+
+  group('test CLIPMode', () {
+
+  });
+
+}

mobile/openapi/test/model_type_test.dart

@@ -0,0 +1,21 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+import 'package:openapi/api.dart';
+import 'package:test/test.dart';
+
+// tests for ModelType
+void main() {
+
+  group('test ModelType', () {
+
+  });
+
+}

mobile/openapi/test/recognition_config_test.dart

@@ -0,0 +1,47 @@
+//
+// AUTO-GENERATED FILE, DO NOT MODIFY!
+//
+// @dart=2.12
+
+// ignore_for_file: unused_element, unused_import
+// ignore_for_file: always_put_required_named_parameters_first
+// ignore_for_file: constant_identifier_names
+// ignore_for_file: lines_longer_than_80_chars
+
+import 'package:openapi/api.dart';
+import 'package:test/test.dart';
+
+// tests for RecognitionConfig
+void main() {
+  // final instance = RecognitionConfig();
+
+  group('test RecognitionConfig', () {
+    // bool enabled
+    test('to test the property `enabled`', () async {
+      // TODO
+    });
+
+    // int maxDistance
+    test('to test the property `maxDistance`', () async {
+      // TODO
+    });
+
+    // int minScore
+    test('to test the property `minScore`', () async {
+      // TODO
+    });
+
+    // String modelName
+    test('to test the property `modelName`', () async {
+      // TODO
+    });
+
+    // ModelType modelType
+    test('to test the property `modelType`', () async {
+      // TODO
+    });
+
+
+  });
+
+}

mobile/openapi/test/system_config_machine_learning_dto_test.dart

@@ -16,23 +16,23 @@ void main() {
   // final instance = SystemConfigMachineLearningDto();
 
   group('test SystemConfigMachineLearningDto', () {
-    // bool clipEncodeEnabled
-    test('to test the property `clipEncodeEnabled`', () async {
+    // ClassificationConfig classification
+    test('to test the property `classification`', () async {
       // TODO
     });
 
-    // bool enabled
-    test('to test the property `enabled`', () async {
+    // CLIPConfig clip
+    test('to test the property `clip`', () async {
       // TODO
     });
 
-    // bool facialRecognitionEnabled
-    test('to test the property `facialRecognitionEnabled`', () async {
+    // bool enabled
+    test('to test the property `enabled`', () async {
       // TODO
     });
 
-    // bool tagImageEnabled
-    test('to test the property `tagImageEnabled`', () async {
+    // RecognitionConfig facialRecognition
+    test('to test the property `facialRecognition`', () async {
       // TODO
     });
 

server/immich-openapi-specs.json

@@ -5354,6 +5354,34 @@
         ],
         "type": "object"
       },
+      "CLIPConfig": {
+        "properties": {
+          "enabled": {
+            "type": "boolean"
+          },
+          "mode": {
+            "$ref": "#/components/schemas/CLIPMode"
+          },
+          "modelName": {
+            "type": "string"
+          },
+          "modelType": {
+            "$ref": "#/components/schemas/ModelType"
+          }
+        },
+        "required": [
+          "enabled",
+          "modelName"
+        ],
+        "type": "object"
+      },
+      "CLIPMode": {
+        "enum": [
+          "vision",
+          "text"
+        ],
+        "type": "string"
+      },
       "ChangePasswordDto": {
         "properties": {
           "newPassword": {
@@ -5432,6 +5460,28 @@
         ],
         "type": "object"
       },
+      "ClassificationConfig": {
+        "properties": {
+          "enabled": {
+            "type": "boolean"
+          },
+          "minScore": {
+            "type": "integer"
+          },
+          "modelName": {
+            "type": "string"
+          },
+          "modelType": {
+            "$ref": "#/components/schemas/ModelType"
+          }
+        },
+        "required": [
+          "minScore",
+          "enabled",
+          "modelName"
+        ],
+        "type": "object"
+      },
       "CreateAlbumDto": {
         "properties": {
           "albumName": {
@@ -6144,6 +6194,14 @@
         ],
         "type": "object"
       },
+      "ModelType": {
+        "enum": [
+          "image-classification",
+          "facial-recognition",
+          "clip"
+        ],
+        "type": "string"
+      },
       "OAuthCallbackDto": {
         "properties": {
           "url": {
@@ -6323,6 +6381,32 @@
         ],
         "type": "object"
       },
+      "RecognitionConfig": {
+        "properties": {
+          "enabled": {
+            "type": "boolean"
+          },
+          "maxDistance": {
+            "type": "integer"
+          },
+          "minScore": {
+            "type": "integer"
+          },
+          "modelName": {
+            "type": "string"
+          },
+          "modelType": {
+            "$ref": "#/components/schemas/ModelType"
+          }
+        },
+        "required": [
+          "minScore",
+          "maxDistance",
+          "enabled",
+          "modelName"
+        ],
+        "type": "object"
+      },
       "SearchAlbumResponseDto": {
         "properties": {
           "count": {
@@ -6968,17 +7052,17 @@
       },
       "SystemConfigMachineLearningDto": {
         "properties": {
-          "clipEncodeEnabled": {
-            "type": "boolean"
+          "classification": {
+            "$ref": "#/components/schemas/ClassificationConfig"
           },
-          "enabled": {
-            "type": "boolean"
+          "clip": {
+            "$ref": "#/components/schemas/CLIPConfig"
           },
-          "facialRecognitionEnabled": {
+          "enabled": {
             "type": "boolean"
           },
-          "tagImageEnabled": {
-            "type": "boolean"
+          "facialRecognition": {
+            "$ref": "#/components/schemas/RecognitionConfig"
           },
           "url": {
             "type": "string"
@@ -6987,9 +7071,9 @@
         "required": [
           "enabled",
           "url",
-          "clipEncodeEnabled",
-          "facialRecognitionEnabled",
-          "tagImageEnabled"
+          "classification",
+          "clip",
+          "facialRecognition"
         ],
         "type": "object"
       },

server/src/domain/facial-recognition/facial-recognition.service.spec.ts

@@ -115,6 +115,7 @@ describe(FacialRecognitionService.name, () => {
     personMock = newPersonRepositoryMock();
     searchMock = newSearchRepositoryMock();
     storageMock = newStorageRepositoryMock();
+    configMock = newSystemConfigRepositoryMock();
 
     mediaMock.crop.mockResolvedValue(croppedFace);
 
@@ -179,9 +180,18 @@ describe(FacialRecognitionService.name, () => {
       machineLearningMock.detectFaces.mockResolvedValue([]);
       assetMock.getByIds.mockResolvedValue([assetStub.image]);
       await sut.handleRecognizeFaces({ id: assetStub.image.id });
-      expect(machineLearningMock.detectFaces).toHaveBeenCalledWith('http://immich-machine-learning:3003', {
-        imagePath: assetStub.image.resizePath,
-      });
+      expect(machineLearningMock.detectFaces).toHaveBeenCalledWith(
+        'http://immich-machine-learning:3003',
+        {
+          imagePath: assetStub.image.resizePath,
+        },
+        {
+          enabled: true,
+          maxDistance: 0.6,
+          minScore: 0.7,
+          modelName: 'buffalo_l',
+        },
+      );
       expect(faceMock.create).not.toHaveBeenCalled();
       expect(jobMock.queue).not.toHaveBeenCalled();
     });

server/src/domain/facial-recognition/facial-recognition.services.ts

@@ -32,7 +32,7 @@ export class FacialRecognitionService {
 
   async handleQueueRecognizeFaces({ force }: IBaseJob) {
     const { machineLearning } = await this.configCore.getConfig();
-    if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) {
+    if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) {
       return true;
     }
 
@@ -59,7 +59,7 @@ export class FacialRecognitionService {
 
   async handleRecognizeFaces({ id }: IEntityJob) {
     const { machineLearning } = await this.configCore.getConfig();
-    if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) {
+    if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) {
       return true;
     }
 
@@ -68,7 +68,11 @@ export class FacialRecognitionService {
       return false;
     }
 
-    const faces = await this.machineLearning.detectFaces(machineLearning.url, { imagePath: asset.resizePath });
+    const faces = await this.machineLearning.detectFaces(
+      machineLearning.url,
+      { imagePath: asset.resizePath },
+      machineLearning.facialRecognition,
+    );
 
     this.logger.debug(`${faces.length} faces detected in ${asset.resizePath}`);
     this.logger.verbose(faces.map((face) => ({ ...face, embedding: `float[${face.embedding.length}]` })));
@@ -80,7 +84,7 @@ export class FacialRecognitionService {
 
       // try to find a matching face and link to the associated person
       // The closer to 0, the better the match. Range is from 0 to 2
-      if (faceSearchResult.total && faceSearchResult.distances[0] < 0.6) {
+      if (faceSearchResult.total && faceSearchResult.distances[0] <= machineLearning.facialRecognition.maxDistance) {
         this.logger.verbose(`Match face with distance ${faceSearchResult.distances[0]}`);
         personId = faceSearchResult.items[0].personId;
       }
@@ -115,7 +119,7 @@ export class FacialRecognitionService {
 
   async handleGenerateFaceThumbnail(data: IFaceThumbnailJob) {
     const { machineLearning } = await this.configCore.getConfig();
-    if (!machineLearning.enabled || !machineLearning.facialRecognitionEnabled) {
+    if (!machineLearning.enabled || !machineLearning.facialRecognition.enabled) {
       return true;
     }
 

server/src/domain/search/search.repository.ts

@@ -86,6 +86,7 @@ export interface ISearchRepository {
   deleteAssets(ids: string[]): Promise<void>;
   deleteFaces(ids: string[]): Promise<void>;
   deleteAllFaces(): Promise<number>;
+  updateCLIPField(num_dim: number): Promise<void>;
 
   searchAlbums(query: string, filters: SearchFilter): Promise<SearchResult<AlbumEntity>>;
   searchAssets(query: string, filters: SearchFilter): Promise<SearchResult<AssetEntity>>;

server/src/domain/search/search.service.ts

@@ -121,15 +121,18 @@ export class SearchService {
     await this.configCore.requireFeature(FeatureFlag.SEARCH);
 
     const query = dto.q || dto.query || '*';
-    const hasClip = machineLearning.enabled && machineLearning.clipEncodeEnabled;
+    const hasClip = machineLearning.enabled && machineLearning.clip.enabled;
     const strategy = dto.clip && hasClip ? SearchStrategy.CLIP : SearchStrategy.TEXT;
     const filters = { userId: authUser.id, ...dto };
 
     let assets: SearchResult<AssetEntity>;
     switch (strategy) {
       case SearchStrategy.CLIP:
-        const clip = await this.machineLearning.encodeText(machineLearning.url, query);
-        assets = await this.searchRepository.vectorSearch(clip, filters);
+        const {
+          machineLearning: { clip },
+        } = await this.configCore.getConfig();
+        const embedding = await this.machineLearning.encodeText(machineLearning.url, { text: query }, clip);
+        assets = await this.searchRepository.vectorSearch(embedding, filters);
         break;
       case SearchStrategy.TEXT:
       default:

server/src/domain/smart-info/dto/index.ts

@@ -0,0 +1 @@
+export * from './model-config.dto';

server/src/domain/smart-info/dto/model-config.dto.ts

@@ -0,0 +1,50 @@
+import { ApiProperty } from '@nestjs/swagger';
+import { Type } from 'class-transformer';
+import { IsBoolean, IsEnum, IsNotEmpty, IsNumber, IsOptional, IsString, Max, Min } from 'class-validator';
+import { CLIPMode, ModelType } from '../machine-learning.interface';
+
+export class ModelConfig {
+  @IsBoolean()
+  enabled!: boolean;
+
+  @IsString()
+  @IsNotEmpty()
+  modelName!: string;
+
+  @IsEnum(ModelType)
+  @IsOptional()
+  @ApiProperty({ enumName: 'ModelType', enum: ModelType })
+  modelType?: ModelType;
+}
+
+export class ClassificationConfig extends ModelConfig {
+  @IsNumber()
+  @Min(0)
+  @Max(1)
+  @Type(() => Number)
+  @ApiProperty({ type: 'integer' })
+  minScore!: number;
+}
+
+export class CLIPConfig extends ModelConfig {
+  @IsEnum(CLIPMode)
+  @IsOptional()
+  @ApiProperty({ enumName: 'CLIPMode', enum: CLIPMode })
+  mode?: CLIPMode;
+}
+
+export class RecognitionConfig extends ModelConfig {
+  @IsNumber()
+  @Min(0)
+  @Max(1)
+  @Type(() => Number)
+  @ApiProperty({ type: 'integer' })
+  minScore!: number;
+
+  @IsNumber()
+  @Min(0)
+  @Max(2)
+  @Type(() => Number)
+  @ApiProperty({ type: 'integer' })
+  maxDistance!: number;
+}

server/src/domain/smart-info/index.ts

@@ -1,3 +1,4 @@
+export * from './dto';
 export * from './machine-learning.interface';
 export * from './smart-info.repository';
 export * from './smart-info.service';

server/src/domain/smart-info/machine-learning.interface.ts

@@ -1,9 +1,15 @@
+import { ClassificationConfig, CLIPConfig, RecognitionConfig } from './dto';
+
 export const IMachineLearningRepository = 'IMachineLearningRepository';
 
-export interface MachineLearningInput {
+export interface VisionModelInput {
   imagePath: string;
 }
 
+export interface TextModelInput {
+  text: string;
+}
+
 export interface BoundingBox {
   x1: number;
   y1: number;
@@ -19,9 +25,20 @@ export interface DetectFaceResult {
   embedding: number[];
 }
 
+export enum ModelType {
+  IMAGE_CLASSIFICATION = 'image-classification',
+  FACIAL_RECOGNITION = 'facial-recognition',
+  CLIP = 'clip',
+}
+
+export enum CLIPMode {
+  VISION = 'vision',
+  TEXT = 'text',
+}
+
 export interface IMachineLearningRepository {
-  classifyImage(url: string, input: MachineLearningInput): Promise<string[]>;
-  encodeImage(url: string, input: MachineLearningInput): Promise<number[]>;
-  encodeText(url: string, input: string): Promise<number[]>;
-  detectFaces(url: string, input: MachineLearningInput): Promise<DetectFaceResult[]>;
+  classifyImage(url: string, input: VisionModelInput, config: ClassificationConfig): Promise<string[]>;
+  encodeImage(url: string, input: VisionModelInput, config: CLIPConfig): Promise<number[]>;
+  encodeText(url: string, input: TextModelInput, config: CLIPConfig): Promise<number[]>;
+  detectFaces(url: string, input: VisionModelInput, config: RecognitionConfig): Promise<DetectFaceResult[]>;
 }

server/src/domain/smart-info/smart-info.service.spec.ts

@@ -84,9 +84,13 @@ describe(SmartInfoService.name, () => {
 
       await sut.handleClassifyImage({ id: asset.id });
 
-      expect(machineMock.classifyImage).toHaveBeenCalledWith('http://immich-machine-learning:3003', {
-        imagePath: 'path/to/resize.ext',
-      });
+      expect(machineMock.classifyImage).toHaveBeenCalledWith(
+        'http://immich-machine-learning:3003',
+        {
+          imagePath: 'path/to/resize.ext',
+        },
+        { enabled: true, minScore: 0.9, modelName: 'microsoft/resnet-50' },
+      );
       expect(smartMock.upsert).toHaveBeenCalledWith({
         assetId: 'asset-1',
         tags: ['tag1', 'tag2', 'tag3'],
@@ -141,13 +145,16 @@ describe(SmartInfoService.name, () => {
     });
 
     it('should save the returned objects', async () => {
+      smartMock.upsert.mockResolvedValue();
       machineMock.encodeImage.mockResolvedValue([0.01, 0.02, 0.03]);
 
       await sut.handleEncodeClip({ id: asset.id });
 
-      expect(machineMock.encodeImage).toHaveBeenCalledWith('http://immich-machine-learning:3003', {
-        imagePath: 'path/to/resize.ext',
-      });
+      expect(machineMock.encodeImage).toHaveBeenCalledWith(
+        'http://immich-machine-learning:3003',
+        { imagePath: 'path/to/resize.ext' },
+        { enabled: true, modelName: 'ViT-B-32::openai' },
+      );
       expect(smartMock.upsert).toHaveBeenCalledWith({
         assetId: 'asset-1',
         clipEmbedding: [0.01, 0.02, 0.03],

server/src/domain/smart-info/smart-info.service.ts

@@ -22,7 +22,7 @@ export class SmartInfoService {
 
   async handleQueueObjectTagging({ force }: IBaseJob) {
     const { machineLearning } = await this.configCore.getConfig();
-    if (!machineLearning.enabled || !machineLearning.tagImageEnabled) {
+    if (!machineLearning.enabled || !machineLearning.classification.enabled) {
       return true;
     }
 
@@ -43,7 +43,7 @@ export class SmartInfoService {
 
   async handleClassifyImage({ id }: IEntityJob) {
     const { machineLearning } = await this.configCore.getConfig();
-    if (!machineLearning.enabled || !machineLearning.tagImageEnabled) {
+    if (!machineLearning.enabled || !machineLearning.classification.enabled) {
       return true;
     }
 
@@ -52,7 +52,11 @@ export class SmartInfoService {
       return false;
     }
 
-    const tags = await this.machineLearning.classifyImage(machineLearning.url, { imagePath: asset.resizePath });
+    const tags = await this.machineLearning.classifyImage(
+      machineLearning.url,
+      { imagePath: asset.resizePath },
+      machineLearning.classification,
+    );
     await this.repository.upsert({ assetId: asset.id, tags });
 
     return true;
@@ -60,7 +64,7 @@ export class SmartInfoService {
 
   async handleQueueEncodeClip({ force }: IBaseJob) {
     const { machineLearning } = await this.configCore.getConfig();
-    if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) {
+    if (!machineLearning.enabled || !machineLearning.clip.enabled) {
       return true;
     }
 
@@ -81,7 +85,7 @@ export class SmartInfoService {
 
   async handleEncodeClip({ id }: IEntityJob) {
     const { machineLearning } = await this.configCore.getConfig();
-    if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) {
+    if (!machineLearning.enabled || !machineLearning.clip.enabled) {
       return true;
     }
 
@@ -90,7 +94,12 @@ export class SmartInfoService {
       return false;
     }
 
-    const clipEmbedding = await this.machineLearning.encodeImage(machineLearning.url, { imagePath: asset.resizePath });
+    const clipEmbedding = await this.machineLearning.encodeImage(
+      machineLearning.url,
+      { imagePath: asset.resizePath },
+      machineLearning.clip,
+    );
+
     await this.repository.upsert({ assetId: asset.id, clipEmbedding: clipEmbedding });
 
     return true;

server/src/domain/system-config/dto/system-config-machine-learning.dto.ts

@@ -1,4 +1,6 @@
-import { IsBoolean, IsUrl, ValidateIf } from 'class-validator';
+import { ClassificationConfig, CLIPConfig, RecognitionConfig } from '@app/domain';
+import { Type } from 'class-transformer';
+import { IsBoolean, IsObject, IsUrl, ValidateIf, ValidateNested } from 'class-validator';
 
 export class SystemConfigMachineLearningDto {
   @IsBoolean()
@@ -8,12 +10,18 @@ export class SystemConfigMachineLearningDto {
   @ValidateIf((dto) => dto.enabled)
   url!: string;
 
-  @IsBoolean()
-  clipEncodeEnabled!: boolean;
+  @Type(() => ClassificationConfig)
+  @ValidateNested()
+  @IsObject()
+  classification!: ClassificationConfig;
 
-  @IsBoolean()
-  facialRecognitionEnabled!: boolean;
+  @Type(() => CLIPConfig)
+  @ValidateNested()
+  @IsObject()
+  clip!: CLIPConfig;
 
-  @IsBoolean()
-  tagImageEnabled!: boolean;
+  @Type(() => RecognitionConfig)
+  @ValidateNested()
+  @IsObject()
+  facialRecognition!: RecognitionConfig;
 }

server/src/domain/system-config/system-config.core.ts

@@ -47,12 +47,25 @@ export const defaults = Object.freeze<SystemConfig>({
     [QueueName.THUMBNAIL_GENERATION]: { concurrency: 5 },
     [QueueName.VIDEO_CONVERSION]: { concurrency: 1 },
   },
+
   machineLearning: {
     enabled: process.env.IMMICH_MACHINE_LEARNING_ENABLED !== 'false',
     url: process.env.IMMICH_MACHINE_LEARNING_URL || 'http://immich-machine-learning:3003',
-    facialRecognitionEnabled: true,
-    tagImageEnabled: true,
-    clipEncodeEnabled: true,
+    classification: {
+      enabled: true,
+      modelName: 'microsoft/resnet-50',
+      minScore: 0.9,
+    },
+    clip: {
+      enabled: true,
+      modelName: 'ViT-B-32::openai',
+    },
+    facialRecognition: {
+      enabled: true,
+      modelName: 'buffalo_l',
+      minScore: 0.7,
+      maxDistance: 0.6,
+    },
   },
   oauth: {
     enabled: false,
@@ -143,9 +156,9 @@ export class SystemConfigCore {
     const mlEnabled = config.machineLearning.enabled;
 
     return {
-      [FeatureFlag.CLIP_ENCODE]: mlEnabled && config.machineLearning.clipEncodeEnabled,
-      [FeatureFlag.FACIAL_RECOGNITION]: mlEnabled && config.machineLearning.facialRecognitionEnabled,
-      [FeatureFlag.TAG_IMAGE]: mlEnabled && config.machineLearning.tagImageEnabled,
+      [FeatureFlag.CLIP_ENCODE]: mlEnabled && config.machineLearning.clip.enabled,
+      [FeatureFlag.FACIAL_RECOGNITION]: mlEnabled && config.machineLearning.facialRecognition.enabled,
+      [FeatureFlag.TAG_IMAGE]: mlEnabled && config.machineLearning.classification.enabled,
       [FeatureFlag.SIDECAR]: true,
       [FeatureFlag.SEARCH]: process.env.TYPESENSE_ENABLED !== 'false',
 
@@ -230,7 +243,7 @@ export class SystemConfigCore {
       _.set(config, key, value);
     }
 
-    return _.defaultsDeep(config, defaults) as SystemConfig;
+    return plainToClass(SystemConfigDto, _.defaultsDeep(config, defaults));
   }
 
   private async loadFromFile(filepath: string, force = false) {

server/src/domain/system-config/system-config.service.spec.ts

@@ -49,9 +49,21 @@ const updatedConfig = Object.freeze<SystemConfig>({
   machineLearning: {
     enabled: true,
     url: 'http://immich-machine-learning:3003',
-    facialRecognitionEnabled: true,
-    tagImageEnabled: true,
-    clipEncodeEnabled: true,
+    classification: {
+      enabled: true,
+      modelName: 'microsoft/resnet-50',
+      minScore: 0.9,
+    },
+    clip: {
+      enabled: true,
+      modelName: 'ViT-B-32::openai',
+    },
+    facialRecognition: {
+      enabled: true,
+      modelName: 'buffalo_l',
+      minScore: 0.7,
+      maxDistance: 0.6,
+    },
   },
   oauth: {
     autoLaunch: true,

server/src/infra/entities/system-config.entity.ts

@@ -1,4 +1,4 @@
-import { QueueName } from '@app/domain/job/job.constants';
+import { QueueName } from '@app/domain';
 import { Column, Entity, PrimaryColumn } from 'typeorm';
 
 @Entity('system_config')
@@ -39,9 +39,18 @@ export enum SystemConfigKey {
 
   MACHINE_LEARNING_ENABLED = 'machineLearning.enabled',
   MACHINE_LEARNING_URL = 'machineLearning.url',
-  MACHINE_LEARNING_FACIAL_RECOGNITION_ENABLED = 'machineLearning.facialRecognitionEnabled',
-  MACHINE_LEARNING_TAG_IMAGE_ENABLED = 'machineLearning.tagImageEnabled',
-  MACHINE_LEARNING_CLIP_ENCODE_ENABLED = 'machineLearning.clipEncodeEnabled',
+
+  MACHINE_LEARNING_CLASSIFICATION_ENABLED = 'machineLearning.classification.enabled',
+  MACHINE_LEARNING_CLASSIFICATION_MODEL_NAME = 'machineLearning.classification.modelName',
+  MACHINE_LEARNING_CLASSIFICATION_MIN_SCORE = 'machineLearning.classification.minScore',
+
+  MACHINE_LEARNING_CLIP_ENABLED = 'machineLearning.clip.enabled',
+  MACHINE_LEARNING_CLIP_MODEL_NAME = 'machineLearning.clip.modelName',
+
+  MACHINE_LEARNING_FACIAL_RECOGNITION_ENABLED = 'machineLearning.facialRecognition.enabled',
+  MACHINE_LEARNING_FACIAL_RECOGNITION_MODEL_NAME = 'machineLearning.facialRecognition.modelName',
+  MACHINE_LEARNING_FACIAL_RECOGNITION_MIN_SCORE = 'machineLearning.facialRecognition.minScore',
+  MACHINE_LEARNING_FACIAL_RECOGNITION_MAX_DISTANCE = 'machineLearning.facialRecognition.maxDistance',
 
   OAUTH_ENABLED = 'oauth.enabled',
   OAUTH_ISSUER_URL = 'oauth.issuerUrl',
@@ -114,9 +123,21 @@ export interface SystemConfig {
   machineLearning: {
     enabled: boolean;
     url: string;
-    clipEncodeEnabled: boolean;
-    facialRecognitionEnabled: boolean;
-    tagImageEnabled: boolean;
+    classification: {
+      enabled: boolean;
+      modelName: string;
+      minScore: number;
+    };
+    clip: {
+      enabled: boolean;
+      modelName: string;
+    };
+    facialRecognition: {
+      enabled: boolean;
+      modelName: string;
+      minScore: number;
+      maxDistance: number;
+    };
   };
   oauth: {
     enabled: boolean;

server/src/infra/migrations/1693236627291-RenameMLEnableFlags.ts

@@ -0,0 +1,25 @@
+import { MigrationInterface, QueryRunner } from "typeorm"
+
+export class RenameMLEnableFlags1693236627291 implements MigrationInterface {
+    public async up(queryRunner: QueryRunner): Promise<void> {
+        await queryRunner.query(`
+            UPDATE system_config SET key = CASE
+            WHEN key = 'ffmpeg.classificationEnabled' THEN 'ffmpeg.classification.enabled'
+            WHEN key = 'ffmpeg.clipEnabled' THEN 'ffmpeg.clip.enabled'
+            WHEN key = 'ffmpeg.facialRecognitionEnabled' THEN 'ffmpeg.facialRecognition.enabled'
+            ELSE key
+            END
+        `);
+    }
+
+    public async down(queryRunner: QueryRunner): Promise<void> {
+        await queryRunner.query(`
+            UPDATE system_config SET key = CASE
+            WHEN key = 'ffmpeg.classification.enabled' THEN 'ffmpeg.classificationEnabled'
+            WHEN key = 'ffmpeg.clip.enabled' THEN 'ffmpeg.clipEnabled'
+            WHEN key = 'ffmpeg.facialRecognition.enabled' THEN 'ffmpeg.facialRecognitionEnabled'
+            ELSE key
+            END
+        `);
+    }
+}

server/src/infra/repositories/machine-learning.repository.ts

@@ -1,29 +1,65 @@
-import { DetectFaceResult, IMachineLearningRepository, MachineLearningInput } from '@app/domain';
+import {
+  ClassificationConfig,
+  CLIPConfig,
+  CLIPMode,
+  DetectFaceResult,
+  IMachineLearningRepository,
+  ModelConfig,
+  ModelType,
+  RecognitionConfig,
+  TextModelInput,
+  VisionModelInput,
+} from '@app/domain';
 import { Injectable } from '@nestjs/common';
-import axios from 'axios';
-import { createReadStream } from 'fs';
-
-const client = axios.create();
+import { readFile } from 'fs/promises';
 
 @Injectable()
 export class MachineLearningRepository implements IMachineLearningRepository {
-  private post<T>(input: MachineLearningInput, endpoint: string): Promise<T> {
-    return client.post<T>(endpoint, createReadStream(input.imagePath)).then((res) => res.data);
+  private async post<T>(url: string, input: TextModelInput | VisionModelInput, config: ModelConfig): Promise<T> {
+    const formData = await this.getFormData(input, config);
+    const res = await fetch(`${url}/predict`, { method: 'POST', body: formData });
+    return res.json();
+  }
+
+  classifyImage(url: string, input: VisionModelInput, config: ClassificationConfig): Promise<string[]> {
+    return this.post<string[]>(url, input, { ...config, modelType: ModelType.IMAGE_CLASSIFICATION });
   }
 
-  classifyImage(url: string, input: MachineLearningInput): Promise<string[]> {
-    return this.post<string[]>(input, `${url}/image-classifier/tag-image`);
+  detectFaces(url: string, input: VisionModelInput, config: RecognitionConfig): Promise<DetectFaceResult[]> {
+    return this.post<DetectFaceResult[]>(url, input, { ...config, modelType: ModelType.FACIAL_RECOGNITION });
   }
 
-  detectFaces(url: string, input: MachineLearningInput): Promise<DetectFaceResult[]> {
-    return this.post<DetectFaceResult[]>(input, `${url}/facial-recognition/detect-faces`);
+  encodeImage(url: string, input: VisionModelInput, config: CLIPConfig): Promise<number[]> {
+    return this.post<number[]>(url, input, {
+      ...config,
+      modelType: ModelType.CLIP,
+      mode: CLIPMode.VISION,
+    } as CLIPConfig);
   }
 
-  encodeImage(url: string, input: MachineLearningInput): Promise<number[]> {
-    return this.post<number[]>(input, `${url}/sentence-transformer/encode-image`);
+  encodeText(url: string, input: TextModelInput, config: CLIPConfig): Promise<number[]> {
+    return this.post<number[]>(url, input, { ...config, modelType: ModelType.CLIP, mode: CLIPMode.TEXT } as CLIPConfig);
   }
 
-  encodeText(url: string, input: string): Promise<number[]> {
-    return client.post<number[]>(`${url}/sentence-transformer/encode-text`, { text: input }).then((res) => res.data);
+  async getFormData(input: TextModelInput | VisionModelInput, config: ModelConfig): Promise<FormData> {
+    const formData = new FormData();
+    const { modelName, modelType, ...options } = config;
+
+    formData.append('modelName', modelName);
+    if (modelType) {
+      formData.append('modelType', modelType);
+    }
+    if (options) {
+      formData.append('options', JSON.stringify(options));
+    }
+    if ('imagePath' in input) {
+      formData.append('image', new Blob([await readFile(input.imagePath)]));
+    } else if ('text' in input) {
+      formData.append('text', input.text);
+    } else {
+      throw new Error('Invalid input');
+    }
+
+    return formData;
   }
 }

server/src/infra/repositories/typesense.repository.ts

@@ -52,6 +52,8 @@ export class TypesenseRepository implements ISearchRepository {
   private logger = new Logger(TypesenseRepository.name);
 
   private _client: Client | null = null;
+  private _updateCLIPLock = false;
+
   private get client(): Client {
     if (!this._client) {
       throw new Error('Typesense client not available (no apiKey was provided)');
@@ -141,7 +143,7 @@ export class TypesenseRepository implements ISearchRepository {
         await this.updateAlias(collection);
       }
     } catch (error: any) {
-      this.handleError(error);
+      await this.handleError(error);
     }
   }
 
@@ -221,6 +223,30 @@ export class TypesenseRepository implements ISearchRepository {
     return records.num_deleted;
   }
 
+  async deleteAllAssets(): Promise<number> {
+    const records = await this.client.collections(assetSchema.name).documents().delete({ filter_by: 'ownerId:!=null' });
+    return records.num_deleted;
+  }
+
+  async updateCLIPField(num_dim: number): Promise<void> {
+    const clipField = assetSchema.fields?.find((field) => field.name === 'smartInfo.clipEmbedding');
+    if (clipField && !this._updateCLIPLock) {
+      try {
+        this._updateCLIPLock = true;
+        clipField.num_dim = num_dim;
+        await this.deleteAllAssets();
+        await this.client
+          .collections(assetSchema.name)
+          .update({ fields: [{ name: 'smartInfo.clipEmbedding', drop: true } as any, clipField] });
+        this.logger.log(`Successfully updated CLIP dimensions to ${num_dim}`);
+      } catch (err: any) {
+        this.logger.error(`Error while updating CLIP field: ${err.message}`);
+      } finally {
+        this._updateCLIPLock = false;
+      }
+    }
+  }
+
   async delete(collection: SearchCollection, ids: string[]): Promise<void> {
     await this.client
       .collections(schemaMap[collection].name)
@@ -326,21 +352,34 @@ export class TypesenseRepository implements ISearchRepository {
     } as SearchResult<T>;
   }
 
-  private handleError(error: any) {
+  private async handleError(error: any) {
     this.logger.error('Unable to index documents');
     const results = error.importResults || [];
+    let dimsChanged = false;
     for (const result of results) {
       try {
         result.document = JSON.parse(result.document);
+        if (result.error.includes('Field `smartInfo.clipEmbedding` must have')) {
+          dimsChanged = true;
+          this.logger.warn(
+            `CLIP embedding dimensions have changed, now ${result.document.smartInfo.clipEmbedding.length} dims. Updating schema...`,
+          );
+          await this.updateCLIPField(result.document.smartInfo.clipEmbedding.length);
+          break;
+        }
+
         if (result.document?.smartInfo?.clipEmbedding) {
           result.document.smartInfo.clipEmbedding = '<truncated>';
         }
-      } catch {}
+      } catch (err: any) {
+        this.logger.error(`Error while updating CLIP field: ${(err.message, err.stack)}`);
+      }
     }
 
-    this.logger.verbose(JSON.stringify(results, null, 2));
+    if (!dimsChanged) {
+      this.logger.log(JSON.stringify(results, null, 2));
+    }
   }
-
   private async updateAlias(collection: SearchCollection) {
     const schema = schemaMap[collection];
     const alias = await this.client

server/test/repositories/search.repository.mock.ts

@@ -11,6 +11,7 @@ export const newSearchRepositoryMock = (): jest.Mocked<ISearchRepository> => {
     deleteAssets: jest.fn(),
     deleteFaces: jest.fn(),
     deleteAllFaces: jest.fn(),
+    updateCLIPField: jest.fn(),
     searchAssets: jest.fn(),
     searchAlbums: jest.fn(),
     vectorSearch: jest.fn(),

web/src/api/open-api/api.ts

@@ -862,6 +862,53 @@ export interface BulkIdsDto {
      */
     'ids': Array<string>;
 }
+/**
+ * 
+ * @export
+ * @interface CLIPConfig
+ */
+export interface CLIPConfig {
+    /**
+     * 
+     * @type {boolean}
+     * @memberof CLIPConfig
+     */
+    'enabled': boolean;
+    /**
+     * 
+     * @type {CLIPMode}
+     * @memberof CLIPConfig
+     */
+    'mode'?: CLIPMode;
+    /**
+     * 
+     * @type {string}
+     * @memberof CLIPConfig
+     */
+    'modelName': string;
+    /**
+     * 
+     * @type {ModelType}
+     * @memberof CLIPConfig
+     */
+    'modelType'?: ModelType;
+}
+
+
+/**
+ * 
+ * @export
+ * @enum {string}
+ */
+
+export const CLIPMode = {
+    Vision: 'vision',
+    Text: 'text'
+} as const;
+
+export type CLIPMode = typeof CLIPMode[keyof typeof CLIPMode];
+
+
 /**
  * 
  * @export
@@ -951,6 +998,39 @@ export interface CheckExistingAssetsResponseDto {
      */
     'existingIds': Array<string>;
 }
+/**
+ * 
+ * @export
+ * @interface ClassificationConfig
+ */
+export interface ClassificationConfig {
+    /**
+     * 
+     * @type {boolean}
+     * @memberof ClassificationConfig
+     */
+    'enabled': boolean;
+    /**
+     * 
+     * @type {number}
+     * @memberof ClassificationConfig
+     */
+    'minScore': number;
+    /**
+     * 
+     * @type {string}
+     * @memberof ClassificationConfig
+     */
+    'modelName': string;
+    /**
+     * 
+     * @type {ModelType}
+     * @memberof ClassificationConfig
+     */
+    'modelType'?: ModelType;
+}
+
+
 /**
  * 
  * @export
@@ -1766,6 +1846,21 @@ export interface MergePersonDto {
      */
     'ids': Array<string>;
 }
+/**
+ * 
+ * @export
+ * @enum {string}
+ */
+
+export const ModelType = {
+    ImageClassification: 'image-classification',
+    FacialRecognition: 'facial-recognition',
+    Clip: 'clip'
+} as const;
+
+export type ModelType = typeof ModelType[keyof typeof ModelType];
+
+
 /**
  * 
  * @export
@@ -1991,6 +2086,45 @@ export interface QueueStatusDto {
      */
     'isPaused': boolean;
 }
+/**
+ * 
+ * @export
+ * @interface RecognitionConfig
+ */
+export interface RecognitionConfig {
+    /**
+     * 
+     * @type {boolean}
+     * @memberof RecognitionConfig
+     */
+    'enabled': boolean;
+    /**
+     * 
+     * @type {number}
+     * @memberof RecognitionConfig
+     */
+    'maxDistance': number;
+    /**
+     * 
+     * @type {number}
+     * @memberof RecognitionConfig
+     */
+    'minScore': number;
+    /**
+     * 
+     * @type {string}
+     * @memberof RecognitionConfig
+     */
+    'modelName': string;
+    /**
+     * 
+     * @type {ModelType}
+     * @memberof RecognitionConfig
+     */
+    'modelType'?: ModelType;
+}
+
+
 /**
  * 
  * @export
@@ -2803,28 +2937,28 @@ export interface SystemConfigJobDto {
 export interface SystemConfigMachineLearningDto {
     /**
      * 
-     * @type {boolean}
+     * @type {ClassificationConfig}
      * @memberof SystemConfigMachineLearningDto
      */
-    'clipEncodeEnabled': boolean;
+    'classification': ClassificationConfig;
     /**
      * 
-     * @type {boolean}
+     * @type {CLIPConfig}
      * @memberof SystemConfigMachineLearningDto
      */
-    'enabled': boolean;
+    'clip': CLIPConfig;
     /**
      * 
      * @type {boolean}
      * @memberof SystemConfigMachineLearningDto
      */
-    'facialRecognitionEnabled': boolean;
+    'enabled': boolean;
     /**
      * 
-     * @type {boolean}
+     * @type {RecognitionConfig}
      * @memberof SystemConfigMachineLearningDto
      */
-    'tagImageEnabled': boolean;
+    'facialRecognition': RecognitionConfig;
     /**
      * 
      * @type {string}

web/src/lib/components/admin-page/settings/machine-learning-settings/machine-learning-settings.svelte

@@ -4,38 +4,45 @@
     NotificationType,
   } from '$lib/components/shared-components/notification/notification';
   import { handleError } from '$lib/utils/handle-error';
-  import { api, SystemConfigDto } from '@api';
+  import { api, SystemConfigMachineLearningDto } from '@api';
   import { isEqual } from 'lodash-es';
   import { fade } from 'svelte/transition';
   import SettingButtonsRow from '../setting-buttons-row.svelte';
   import SettingInputField, { SettingInputFieldType } from '../setting-input-field.svelte';
   import SettingSwitch from '../setting-switch.svelte';
+  import SettingAccordion from '../setting-accordion.svelte';
+  import SettingSelect from '../setting-select.svelte';
 
+  export let machineLearningConfig: SystemConfigMachineLearningDto; // this is the config that is being edited
   export let disabled = false;
 
-  let config: SystemConfigDto;
-  let defaultConfig: SystemConfigDto;
+  let savedConfig: SystemConfigMachineLearningDto;
+  let defaultConfig: SystemConfigMachineLearningDto;
 
   async function refreshConfig() {
-    [config, defaultConfig] = await Promise.all([
-      api.systemConfigApi.getConfig().then((res) => res.data),
-      api.systemConfigApi.getDefaults().then((res) => res.data),
+    [savedConfig, defaultConfig] = await Promise.all([
+      api.systemConfigApi.getConfig().then((res) => res.data.machineLearning),
+      api.systemConfigApi.getDefaults().then((res) => res.data.machineLearning),
     ]);
   }
 
   async function reset() {
     const { data: resetConfig } = await api.systemConfigApi.getConfig();
-    config = resetConfig;
+    machineLearningConfig = { ...resetConfig.machineLearning };
+    savedConfig = { ...resetConfig.machineLearning };
     notificationController.show({ message: 'Reset to the last saved settings', type: NotificationType.Info });
   }
 
   async function saveSetting() {
     try {
       const { data: current } = await api.systemConfigApi.getConfig();
-      await api.systemConfigApi.updateConfig({
-        systemConfigDto: { ...current, machineLearning: config.machineLearning },
+      const result = await api.systemConfigApi.updateConfig({
+        systemConfigDto: { ...current, machineLearning: machineLearningConfig },
       });
-      await refreshConfig();
+
+      machineLearningConfig = { ...result.data.machineLearning };
+      savedConfig = { ...result.data.machineLearning };
+
       notificationController.show({ message: 'Settings saved', type: NotificationType.Info });
     } catch (error) {
       handleError(error, 'Unable to save settings');
@@ -43,10 +50,7 @@
   }
 
   async function resetToDefault() {
-    await refreshConfig();
-    const { data: defaults } = await api.systemConfigApi.getDefaults();
-    config = defaults;
-
+    machineLearningConfig = { ...defaultConfig };
     notificationController.show({ message: 'Reset settings to defaults', type: NotificationType.Info });
   }
 </script>
@@ -54,52 +58,152 @@
 <div class="mt-2">
   {#await refreshConfig() then}
     <div in:fade={{ duration: 500 }}>
-      <form autocomplete="off" on:submit|preventDefault class="mx-4 flex flex-col gap-4 py-4">
-        <SettingSwitch
-          title="Enabled"
-          subtitle="Use machine learning features"
-          {disabled}
-          bind:checked={config.machineLearning.enabled}
-        />
+      <form autocomplete="off" on:submit|preventDefault class="mx-4 mt-4">
+        <div class="flex flex-col gap-4">
+          <SettingSwitch
+            title="ENABLED"
+            subtitle="If disabled, all ML features will be disabled regardless of the below settings."
+            {disabled}
+            bind:checked={machineLearningConfig.enabled}
+          />
 
-        <hr />
+          <hr />
 
-        <SettingInputField
-          inputType={SettingInputFieldType.TEXT}
-          label="URL"
-          desc="URL of machine learning server"
-          bind:value={config.machineLearning.url}
-          required={true}
-          disabled={disabled || !config.machineLearning.enabled}
-          isEdited={!(config.machineLearning.url === config.machineLearning.url)}
-        />
+          <SettingInputField
+            inputType={SettingInputFieldType.TEXT}
+            label="URL"
+            desc="URL of the machine learning server"
+            bind:value={machineLearningConfig.url}
+            required={true}
+            disabled={disabled || !machineLearningConfig.enabled}
+            isEdited={machineLearningConfig.url !== savedConfig.url}
+          />
+        </div>
 
-        <SettingSwitch
-          title="SMART SEARCH"
-          subtitle="Extract CLIP embeddings for smart search"
-          bind:checked={config.machineLearning.clipEncodeEnabled}
-          disabled={disabled || !config.machineLearning.enabled}
-        />
+        <SettingAccordion title="Image Tagging" subtitle="Tag and classify images with object labels">
+          <div class="ml-4 mt-4 flex flex-col gap-4">
+            <SettingSwitch
+              title="ENABLED"
+              subtitle="If disabled, images will not be tagged. This affects the Things section in the Explore page as well as 'm:' searches."
+              bind:checked={machineLearningConfig.classification.enabled}
+              disabled={disabled || !machineLearningConfig.enabled}
+            />
 
-        <SettingSwitch
-          title="FACIAL RECOGNITION"
-          subtitle="Recognize and group faces in photos"
-          disabled={disabled || !config.machineLearning.enabled}
-          bind:checked={config.machineLearning.facialRecognitionEnabled}
-        />
+            <hr />
 
-        <SettingSwitch
-          title="IMAGE TAGGING"
-          subtitle="Tag and classify images"
-          disabled={disabled || !config.machineLearning.enabled}
-          bind:checked={config.machineLearning.tagImageEnabled}
-        />
+            <SettingInputField
+              inputType={SettingInputFieldType.TEXT}
+              label="IMAGE CLASSIFICATION MODEL"
+              bind:value={machineLearningConfig.classification.modelName}
+              required={true}
+              disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.classification.enabled}
+              isEdited={machineLearningConfig.classification.modelName !== savedConfig.classification.modelName}
+            >
+              <p slot="desc" class="immich-form-label pb-2 text-sm">
+                The name of an image classification model listed <a
+                  href="https://huggingface.co/models?pipeline_tag=image-classification&sort=trending"><u>here</u></a
+                >. It must be tagged with the 'Image Classification' task and must support ONNX conversion.
+              </p>
+            </SettingInputField>
+
+            <SettingInputField
+              inputType={SettingInputFieldType.NUMBER}
+              label="IMAGE CLASSIFICATION THRESHOLD"
+              desc="Minimum confidence score to add a particular object tag. Lower values will add more tags to images, but may result in more false positives. Will not have any effect until the Tag Objects job is re-run."
+              bind:value={machineLearningConfig.classification.minScore}
+              step="0.1"
+              min="0"
+              max="1"
+              disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.classification.enabled}
+              isEdited={machineLearningConfig.classification.minScore !== savedConfig.classification.minScore}
+            />
+          </div>
+        </SettingAccordion>
+
+        <SettingAccordion title="Smart Search" subtitle="Search for images semantically using CLIP embeddings">
+          <div class="ml-4 mt-4 flex flex-col gap-4">
+            <SettingSwitch
+              title="ENABLED"
+              subtitle="If disabled, images will not be encoded for smart search."
+              bind:checked={machineLearningConfig.clip.enabled}
+              disabled={disabled || !machineLearningConfig.enabled}
+            />
+
+            <hr />
+
+            <SettingInputField
+              inputType={SettingInputFieldType.TEXT}
+              label="CLIP MODEL"
+              bind:value={machineLearningConfig.clip.modelName}
+              required={true}
+              disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.clip.enabled}
+              isEdited={machineLearningConfig.clip.modelName !== savedConfig.clip.modelName}
+            >
+              <p slot="desc" class="immich-form-label pb-2 text-sm">
+                The name of a CLIP model listed <a
+                  href="https://clip-as-service.jina.ai/user-guides/benchmark/#size-and-efficiency"><u>here</u></a
+                >. Note that you must re-run the 'Encode CLIP' job for all images upon changing a model.
+              </p>
+            </SettingInputField>
+          </div>
+        </SettingAccordion>
+
+        <SettingAccordion title="Facial Recognition" subtitle="Detect, recognize and group faces in images">
+          <div class="ml-4 mt-4 flex flex-col gap-4">
+            <SettingSwitch
+              title="ENABLED"
+              subtitle="If disabled, images will not be encoded for facial recognition and will not populate the People section in the Explore page."
+              bind:checked={machineLearningConfig.facialRecognition.enabled}
+              disabled={disabled || !machineLearningConfig.enabled}
+            />
+
+            <hr />
+
+            <SettingSelect
+              label="FACIAL RECOGNITION MODEL"
+              desc="Smaller models are faster and use less memory, but perform worse. Note that you must re-run the Recognize Faces job for all images upon changing a model."
+              name="facial-recognition-model"
+              bind:value={machineLearningConfig.facialRecognition.modelName}
+              options={[
+                { value: 'buffalo_l', text: 'buffalo_l' },
+                { value: 'buffalo_s', text: 'buffalo_s' },
+              ]}
+              disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.facialRecognition.enabled}
+              isEdited={machineLearningConfig.facialRecognition.modelName !== savedConfig.facialRecognition.modelName}
+            />
+
+            <SettingInputField
+              inputType={SettingInputFieldType.NUMBER}
+              label="MIN DETECTION SCORE"
+              desc="Minimum confidence score for a face to be detected from 0-1. Lower values will detect more faces but may result in false positives."
+              bind:value={machineLearningConfig.facialRecognition.minScore}
+              step="0.1"
+              min="0"
+              max="1"
+              disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.facialRecognition.enabled}
+              isEdited={machineLearningConfig.facialRecognition.minScore !== savedConfig.facialRecognition.minScore}
+            />
+
+            <SettingInputField
+              inputType={SettingInputFieldType.NUMBER}
+              label="MAX RECOGNITION DISTANCE"
+              desc="Maximum distance between two faces to be considered the same person, ranging from 0-2. Lowering this can prevent labeling two people as the same person, while raising it can prevent labeling the same person as two different people. Note that it is easier to merge two people than to split one person in two, so err on the side of a lower threshold when possible."
+              bind:value={machineLearningConfig.facialRecognition.maxDistance}
+              step="0.1"
+              min="0"
+              max="2"
+              disabled={disabled || !machineLearningConfig.enabled || !machineLearningConfig.facialRecognition.enabled}
+              isEdited={machineLearningConfig.facialRecognition.maxDistance !==
+                savedConfig.facialRecognition.maxDistance}
+            />
+          </div>
+        </SettingAccordion>
 
         <SettingButtonsRow
           on:reset={reset}
           on:save={saveSetting}
           on:reset-to-default={resetToDefault}
-          showResetToDefault={!isEqual(config, defaultConfig)}
+          showResetToDefault={!isEqual(savedConfig, defaultConfig)}
           {disabled}
         />
       </form>

web/src/lib/components/admin-page/settings/setting-input-field.svelte

@@ -13,6 +13,9 @@
 
   export let inputType: SettingInputFieldType;
   export let value: string | number;
+  export let min = Number.MIN_VALUE.toString();
+  export let max = Number.MAX_VALUE.toString();
+  export let step = '1';
   export let label = '';
   export let desc = '';
   export let required = false;
@@ -48,6 +51,8 @@
     <p class="immich-form-label pb-2 text-sm" id="{label}-desc">
       {desc}
     </p>
+  {:else}
+    <slot name="desc" />
   {/if}
 
   <input
@@ -57,6 +62,9 @@
     id={label}
     name={label}
     type={inputType}
+    {min}
+    {max}
+    {step}
     {required}
     {value}
     on:input={handleInput}

web/src/routes/admin/system-settings/+page.svelte

@@ -68,6 +68,10 @@
       <FFmpegSettings disabled={$featureFlags.configFile} ffmpegConfig={configs.ffmpeg} />
     </SettingAccordion>
 
+    <SettingAccordion title="Machine Learning Settings" subtitle="Manage model settings">
+      <MachineLearningSettings disabled={$featureFlags.configFile} machineLearningConfig={configs.machineLearning} />
+    </SettingAccordion>
+
     <SettingAccordion
       title="Job Settings"
       subtitle="Manage job concurrency"
@@ -84,10 +88,6 @@
       <OAuthSettings disabled={$featureFlags.configFile} oauthConfig={configs.oauth} />
     </SettingAccordion>
 
-    <SettingAccordion title="Machine Learning" subtitle="Manage machine learning settings">
-      <MachineLearningSettings disabled={$featureFlags.configFile} />
-    </SettingAccordion>
-
     <SettingAccordion
       title="Storage Template"
       subtitle="Manage the folder structure and file name of the upload asset"