app.py

import gradio as gr
from diffusers import DiffusionPipeline
import random

pipe = DiffusionPipeline.from_pretrained("UnfilteredAI/NSFW-gen-v2")

def generate_image(prompt, negative_prompt="", height=1024, width=1024, seed=None):
    generator = None
    if seed is not None:
        generator = torch.Generator(device="cuda").manual_seed(seed)
    
    images = pipe(prompt, negative_prompt=negative_prompt, height=height, width=width, generator=generator).images
    return images[0]

# Define the Gradio interface
inputs = [
    gr.inputs.Textbox(label="Prompt", default="A fantasy landscape", lines=2),
    gr.inputs.Textbox(label="Negative Prompt", default="", lines=2),
    gr.inputs.Slider(minimum=256, maximum=1024, step=64, default=1024, label="Height"),
    gr.inputs.Slider(minimum=256, maximum=1024, step=64, default=1024, label="Width"),
    gr.inputs.Number(default=None, label="Seed", optional=True)
]

outputs = gr.outputs.Image(type="pil", label="Generated Image")

gr.Interface(fn=generate_image, inputs=inputs, outputs=outputs, title="Stable Diffusion Image Generator").launch()