import gradio as gr
import torch
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler

model_id = "stabilityai/stable-diffusion-2-1"

# Use the DPMSolverMultistepScheduler (DPM-Solver++) scheduler here instead
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

def diffusion(text,num_inference_steps,guidance_scale):
    prompt = text
    image = pipe(prompt,guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
    return image
demo = gr.Interface(
    diffusion,
    [
        gr.Textbox(
            label="prompt text",
            lines=3,
        ),
        gr.Slider(1, 100, value=50),
        gr.Slider(1.0, 30.0, value=7.5),
    ],
    "image",
   
)
if __name__ == "__main__":
    demo.launch()

    
image.save("astronaut_rides_horse.png")