app.py

import os
import gradio as gr
import torch
from diffusers import StableDiffusion3Pipeline

def image_generation(prompt):
    device = "cuda" if torch.cuda.is_available() else "cpu"
    # Retrieve the token from the environment variable
    huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
    print(os.getenv("HUGGINGFACE_TOKEN"))

    pipeline = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", 
                                                        torch_dtype=torch.float16 if device == "cuda" else torch.float32,
                                                        text_encoder_3=None,
                                                        tokenizer_3=None)
    pipeline.enable_model_cpu_offload

    image = pipeline(
        prompt=prompt,
        negative_prompt="blurred, ugly, watermark, low resolution, blurry",
        num_inference_steps=30,
        height=1024,
        width=1024,
        guidance_scale=9.0
    ).images[0]

    return image

interface= gr.Interface(
    fn=image_generation,
    inputs = gr.Textbox(lines=2, placeholder="Enter your Prompt..."),
    outputs = gr.Image(type="pil"),
    title ="@GenAiLearnivers Project 9: Image creation using Stable Diffusion 3 Model",
    description="This application will be used to generate awesome images using SD3 model"
)

interface.launch()