from diffusers import StableDiffusionXLPipeline
import torch
from gradio import Interface, Image, Dropdown, Slider
import gradio as gr
import spaces

model_id = "RunDiffusion/Juggernaut-X-v10"
pipe = StableDiffusionXLPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

@spaces.GPU()
def text_to_image(prompt, negative_prompt, steps, guidance_scale, add_4k_masterpiece, progress=gr.Progress(track_tqdm=True)):
    if add_4k_masterpiece:
        prompt += ", 4k, (masterpiece)"
    image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=guidance_scale).images[0]
    return image
# duplicate_button = gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")

gradio_interface = Interface(
    fn=text_to_image,
    allow_duplication=False,
    inputs=[
        gr.Textbox(label="Prompt", lines=2, placeholder="Enter your prompt here..."),
        gr.Textbox(label="Negative Prompt", lines=2, placeholder="What to exclude from the image..."),
        gr.Slider(minimum=1, maximum=65, value=50, label="Steps", step=1),
        gr.Slider(minimum=1, maximum=20, value=7.5, label="Guidance Scale", step=0.1),
        gr.Checkbox(label="Add recommended prompt items (4k, masterpiece)", value=False)
    ],
    outputs=Image(type="pil", show_download_button=True),
    examples=[
     ["1 young woman , 18 yo , full body shot , perfect teen body , Photorealistic, real photo,"],
    ],
    cache_examples=False,
    theme=gr.themes.Soft()
)

gradio_interface.launch()