app.py

import gradio as gr
from huggingface_hub import InferenceClient
from PIL import Image
import io

# Initialize the client (Uses Hugging Face's free inference API)
client = InferenceClient("lllyasviel/sd-controlnet-scribble")

def generate_image(sketch, prompt):
    if sketch is None:
        return None
    
    # The model expects a prompt to guide the style
    full_prompt = f"Professional photography, high quality, realistic, {prompt}"
    
    # Generate the image
    # Note: 'sketch' from Gradio is a dictionary with 'composite' or a PIL image
    image = client.image_to_image(sketch, prompt=full_prompt)
    return image

# Build a stylish UI
with gr.Blocks() as demo:
    gr.Markdown("# 🎨 Sketch-to-Photo AI")
    gr.Markdown("Draw something simple on the left, type what it is, and watch it turn into a photo!")
    
    with gr.Row():
        with gr.Column():
            # The Sketchpad input
            input_sketch = gr.Sketchpad(type="pil", label="Draw Here")
            prompt_input = gr.Textbox(placeholder="What did you draw? (e.g., 'A sunset over mountains')", label="Description")
            btn = gr.Button("Magic Generate ✨")
        
        with gr.Column():
            output_image = gr.Image(label="AI Result")

    btn.click(fn=generate_image, inputs=[input_sketch, prompt_input], outputs=output_image, show_progress=True)

if __name__ == "__main__":
    demo.launch()