"""
ONNX Runtime backend — default CPU inference for all vision models.

Each create_* method returns a concrete implementation of the
corresponding ABC from base.py. Models are loaded from ONNX files
under settings.vision.models_dir, downloaded on first boot by
bootstrap_models.py.
"""
import logging

from app.config import VisionSettings
from app.services.vision.base import Embedder, OCREngine, ObjectDetector, FaceProcessor, ContentClassifier

logger = logging.getLogger(__name__)


class ONNXBackend:
    """Factory for ONNX Runtime-based vision model instances."""

    def __init__(self, vision_settings: VisionSettings):
        self._settings = vision_settings

    def create_embedder(self) -> Embedder:
        model_name = self._settings.embedder.name
        if model_name.startswith("siglip2"):
            from app.services.vision.embed import SigLIP2Embedder
            return SigLIP2Embedder(self._settings)
        else:
            from app.services.vision.embed import OpenCLIPEmbedder
            return OpenCLIPEmbedder(self._settings)

    def create_ocr(self) -> OCREngine:
        from app.services.vision.ocr import RapidOCREngine
        return RapidOCREngine(self._settings)

    def create_detector(self) -> ObjectDetector:
        from app.services.vision.detect import YOLOv8Detector
        return YOLOv8Detector(self._settings)

    def create_face_processor(self) -> FaceProcessor:
        from app.services.vision.insightface_processor import InsightFaceProcessor
        return InsightFaceProcessor(self._settings)

    def create_classifier(self) -> ContentClassifier:
        from app.services.vision.classify import CLIPContentClassifier
        return CLIPContentClassifier(self._settings)