import logging
from PIL import Image
from huggingface_hub import InferenceClient

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)


class DiffusionClient:
    def __init__(
        self,
        model_id: str = "black-forest-labs/FLUX.1-schnell",
        hf_token: str | None = None,
        provider: str = "auto",
    ):
        self.model_id = model_id
        _token = hf_token if hf_token else None
        self.client = InferenceClient(api_key=_token, provider=provider)
        self._ready = False

    def load_model(self):
        if self._ready:
            logger.info("Image API client already ready. Skipping.")
            return
        logger.info(
            "Image API client ready (model=%s, serverless inference).", self.model_id
        )
        self._ready = True

    def gen_image(
        self,
        prompt: str,
        negative_prompt: str = "",
        num_inference_steps: int = 4,
        guidance_scale: float = 0.0,
        width: int = 768,
        height: int = 768,
    ) -> Image.Image | None:
        if not self._ready:
            self.load_model()

        try:
            image = self.client.text_to_image(
                prompt=prompt,
                model=self.model_id,
                negative_prompt=negative_prompt or None,
                num_inference_steps=num_inference_steps,
                guidance_scale=guidance_scale,
                width=width,
                height=height,
            )
            return image
        except Exception:
            logger.exception("Image generation failed for prompt: %.120s", prompt)
            raise