app.py

import gradio as gr

def greet(name):
    return "results " + name + "!!"

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()

#When running locally, you won`t have access to this, so you can remove this part
word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
word_list = word_list_dataset["train"]['text']

is_gpu_busy = False
def infer(prompt):
    global is_gpu_busy
    samples = 4
    steps = 50
    scale = 7.9
    #When running locally you can also remove this filter
    for filter in word_list:
        if re.search(rf"\b{filter}\b", prompt):
            raise gr.Error("Unsafe content found. Please try again with different prompts.")
        
    #generator = torch.Generator(device=device).manual_seed(seed)
    #print("Is GPU busy? ", is_gpu_busy)
    images = []
    #if(not is_gpu_busy):
    #    is_gpu_busy = True