class ImageAnalysisAgent:
    """
    Lazy image-analysis router.

    It loads each computer-vision model only when that image type is requested,
    so the API can start even if a heavy model has not been downloaded yet.
    """

    def __init__(self, config):
        self.config = config
        self._classifier = None
        self._chest_xray_agent = None
        self._skin_lesion_agent = None

    @property
    def image_classifier(self):
        if self._classifier is None:
            from .image_classifier import ImageClassifier

            self._classifier = ImageClassifier(vision_model=self.config.medical_cv.llm)
        return self._classifier

    @property
    def chest_xray_agent(self):
        if self._chest_xray_agent is None:
            from .chest_xray_agent.covid_chest_xray_inference import ChestXRayClassification

            self._chest_xray_agent = ChestXRayClassification(
                model_path=self.config.medical_cv.chest_xray_model_path
            )
        return self._chest_xray_agent

    @property
    def skin_lesion_agent(self):
        if self._skin_lesion_agent is None:
            from .skin_lesion_agent.skin_lesion_inference import SkinLesionSegmentation

            self._skin_lesion_agent = SkinLesionSegmentation(
                model_path=self.config.medical_cv.skin_lesion_model_path
            )
        return self._skin_lesion_agent

    def analyze_image(self, image_path: str) -> str:
        return self.image_classifier.classify_image(image_path)

    def classify_chest_xray(self, image_path: str) -> str:
        return self.chest_xray_agent.predict(image_path)

    def segment_skin_lesion(self, image_path: str) -> str:
        return self.skin_lesion_agent.predict(
            image_path,
            self.config.medical_cv.skin_lesion_segmentation_output_path,
        )