import json
import uuid
from pathlib import Path

import numpy as np
from PIL import Image

import folder_paths


def comfy_batch_to_temp_images(image_batch, prefix="fl_vlm"):
    if image_batch is None:
        raise ValueError("FL VLM Image Inference requires an IMAGE input.")

    temp_dir = Path(folder_paths.temp_directory) / "fl_vlm"
    temp_dir.mkdir(parents=True, exist_ok=True)

    paths = []
    for idx in range(int(image_batch.shape[0])):
        array = image_batch[idx].detach().cpu().numpy()
        array = np.clip(array * 255.0, 0, 255).astype(np.uint8)
        path = temp_dir / f"{prefix}_{idx}_{uuid.uuid4().hex}.png"
        Image.fromarray(array).save(path)
        paths.append(path)
    return paths


def remove_temp_images(paths):
    for path in paths:
        try:
            Path(path).unlink(missing_ok=True)
        except Exception:
            pass


def compact_json(data):
    return json.dumps(data, ensure_ascii=False, indent=2)