app.py

import gradio as gr
from PIL import Image
from utils import generate_thumbnail

def process(image, text, font_size, position, text_color):
    result = generate_thumbnail(image, text, font_size=font_size, position=position, text_color=text_color)
    return result

demo = gr.Interface(
    fn=process,
    inputs=[
        gr.Image(type="pil", label="Upload Background Image"),
        gr.Textbox(label="Thumbnail Text"),
        gr.Slider(20, 100, step=5, value=60, label="Font Size"),
        gr.Radio(["top", "center", "bottom"], label="Text Position", value="bottom"),
        gr.ColorPicker(label="Text Color", value="#FFFFFF"),
    ],
    outputs=gr.Image(label="Generated Thumbnail"),
    title="🖼️ AI Thumbnail Generator",
    description="Upload an image and generate a custom thumbnail with your text.",
    allow_flagging="never"
)

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

    from diffusers import StableDiffusionPipeline
import torch

# Load model from Hugging Face Hub
pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",  # You can use another model if needed
    torch_dtype=torch.float16,
    use_safetensors=True,
    revision="fp16"
)

# Move to GPU if available
pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")

# Generate an image
prompt = "A Minecraft player standing on a hill during sunset, pixel art style"
image = pipe(prompt).images[0]

# Save the image
image.save("minecraft_thumbnail.png")