import logging

log = logging.getLogger("tell")

# CLIP zero-shot prompts. Wording matters a lot here, so test changes on real uploads.
LABELS = {
    "chart": "a bar chart or line graph with axes",
    "screenshot": "a screenshot of a social media post or a text message conversation",
    "photo": "a photo, painting, meme, or AI-generated picture",
}

_clf = None


def classify_image(image, threshold: float = 0.5) -> tuple[str, float]:
    global _clf
    try:
        if _clf is None:
            from transformers import pipeline
            _clf = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32")
        top = _clf(image, candidate_labels=list(LABELS.values()))[0]
    except Exception as e:
        log.warning("Classifier failed: %s", e)
        return "unknown", 0.0

    if top["score"] < threshold:
        return "unknown", top["score"]
    kind = next(k for k, v in LABELS.items() if v == top["label"])
    return kind, top["score"]