import os
import logging
import numpy as np
import cv2
from dotenv import load_dotenv
from huggingface_hub import InferenceClient, HfFolder
from PIL import Image

load_dotenv()

# Acquire token
hf_token = os.getenv("HUGGING_FACE_HUB_TOKEN") or HfFolder.get_token()
if not hf_token:
    print("❌ No Hugging Face token found. Signature generation will fail.")
    CLIENT = None
else:
    print("✅ Using Hugging Face token for signature generation.")
    CLIENT = InferenceClient(token=hf_token)

MODEL_ID = "stabilityai/stable-diffusion-xl-base-1.0"

def generate_signatures(name: str, num_variations: int = 3) -> list:
    """Generates multiple signature variations for a given name."""
    if CLIENT is None:
        return []

    prompts = [
        f"A clean, elegant, handwritten signature of the name '{name}' on a plain white background. Cursive, professional.",
        f"Calligraphy signature of '{name}'. Black ink on white paper. Minimalist, artistic.",
        f"A doctor's signature for '{name}'. Quick, scribbled, but legible. Official-looking script."
    ]
    images = []
    for i in range(num_variations):
        prompt = prompts[i % len(prompts)]
        logging.info(f"Generating signature variation {i+1} for '{name}'…")
        try:
            pil_img = CLIENT.text_to_image(
                prompt,
                model=MODEL_ID,
                negative_prompt=(
                    "photograph, text, multiple signatures, watermark, blurry, colorful, background"
                ),
                guidance_scale=8.0
            )
            np_img = np.array(pil_img)
            cv_img = cv2.cvtColor(np_img, cv2.COLOR_RGB2BGR)
            images.append(cv_img)
        except Exception as e:
            logging.error(f"❌ Signature generation failed: {e}")
    return images