import gradio as gr
import requests
import qrcode
import io
from PIL import Image, ImageDraw

import os

# Get the Hugging Face API token from the environment variable
hf_token = os.environ.get("hf_token")

# Function to generate a QR code
def generate_qr_image(url, image_size):
    qr = qrcode.QRCode(
        version=1,
        error_correction=qrcode.constants.ERROR_CORRECT_L,
        box_size=10,
        border=4,
    )
    qr.add_data(url)
    qr.make(fit=True)

    qr_img = qr.make_image(fill_color="black", back_color="white").convert("RGBA")
    
    # Resize the QR code to cover the entire image area
    qr_img = qr_img.resize((image_size[0], image_size[1]))
    
    return qr_img

# Function to query the image from the Hugging Face API
def query_image(text):
    API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/realistic-vision-v51"
    headers = {"Authorization": f"Bearer {hf_token}"}

    response = requests.post(API_URL, headers=headers, json={"inputs": text})
    return response.content

# Gradio app function
def generate_image(url, text):
    # Generate image from Hugging Face API
    image_bytes = query_image(text)
    api_image = Image.open(io.BytesIO(image_bytes))
    
    # Generate QR code image
    qr_image = generate_qr_image(url, api_image.size)
    
    # Blend the API image and QR code
    final_image = Image.alpha_composite(api_image, qr_image)
    
    return final_image

# Inputs and outputs for Gradio interface
inputs = [
    gr.Textbox(lines=1, label="URL"),
    gr.Textbox(lines=2, label="Prompt for Image"),
]
output = gr.Image(type="pil", label="Generated Image")

# Gradio app interface
gr.Interface(fn=generate_image, inputs=inputs, outputs=output, title="QR Code Image Generator", description="Generate an image with a QR code linked to the input URL and an image from the Hugging Face API", theme="soft").launch()