app.py

import gradio as gr
from huggingface_hub import InferenceClient

# Using FLUX.1-schnell, a state-of-the-art incredible image generation model available free on HF API
try:
    client = InferenceClient("black-forest-labs/FLUX.1-schnell")
except Exception as e:
    client = None

def generate_image(prompt, progress=gr.Progress()):
    if not client:
        return None
    try:
        progress(0.5, desc="Generating Artwork (This takes a few seconds)...")
        # Generate image using HF Serverless API
        image = client.text_to_image(prompt)
        progress(1.0, desc="Done!")
        return image
    except Exception as e:
        raise gr.Error(f"FLUX Inference Failed: {str(e)}")

# A sleek Gradio interface
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🎨 FLUX.1 AI Image Studio")
    gr.Markdown("Generate stunning, hyperrealistic images in seconds using the open-source **FLUX.1-schnell** model via the Hugging Face Serverless API.")
    
    with gr.Row():
        with gr.Column(scale=1):
            prompt = gr.Textbox(label="Prompt", placeholder="A cyberpunk cat hacker in neon lights, highly detailed, 4k...", lines=4)
            btn = gr.Button("Generate Artwork 🪄", variant="primary")
            
            gr.Markdown("### Try these Examples:")
            gr.Examples(
                examples=[
                    ["A futuristic city built into a giant tree, cinematic lighting, conceptual art"], 
                    ["An astronaut riding a glowing translucent horse on the surface of Mars, 8k resolution"]
                ],
                inputs=[prompt]
            )
        with gr.Column(scale=1):
            output = gr.Image(label="Generated Artwork", type="pil")
            
    btn.click(generate_image, inputs=prompt, outputs=output)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0")