import cv2

def enhance_image_for_ai(input_path: str) -> str:
    """Smooths camera sensor noise and brightens dark areas for vision LLMs."""
    img = cv2.imread(input_path)
    if img is None:
        return input_path

    # 1. Remove ISO sensor noise (grain)
    denoised = cv2.fastNlMeansDenoisingColored(img, None, h=7, hColor=7, templateWindowSize=7, searchWindowSize=21)

    # 2. Convert to LAB color space for luminance enhancement
    lab = cv2.cvtColor(denoised, cv2.COLOR_BGR2LAB)
    l, a, b = cv2.split(lab)

    # 3. Apply softer CLAHE (lower clipLimit prevents noise amplification)
    clahe = cv2.createCLAHE(clipLimit=1.8, tileGridSize=(8, 8))
    cl = clahe.apply(l)

    # 4. Merge channels back
    limg = cv2.merge((cl, a, b))
    enhanced = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)

    enhanced_path = input_path.replace(".jpg", "_enhanced.jpg")
    cv2.imwrite(enhanced_path, enhanced, [cv2.IMWRITE_JPEG_QUALITY, 90])
    return enhanced_path