app.py

import gradio as gr
import os
import requests
import json
from huggingface_hub import login

from css_html_js import custom_css

from about import (
    CITATION_BUTTON_LABEL,
    CITATION_BUTTON_TEXT,
    EVALUATION_QUEUE_TEXT,
    INTRODUCTION_TEXT,
    LLM_BENCHMARKS_TEXT,
    TITLE,
)

myip = "0.0.0.0"
myport=80
is_spaces = True if "SPACE_ID" in os.environ else False
is_shared_ui = False


with gr.Blocks() as demo:
    gr.HTML(TITLE)
    gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
    with gr.Row() as advlearn:
        drop = gr.Dropdown(["Object-Church", "Object-Parachute", "Object-Garbage_Truck","Object-Tench",
                            "Style-Van_Gogh","Concept-Nudity"], 
                               label="Unlearning undesirable")
        with gr.Column():
                # gr.Markdown("Please upload your model id.")
                drop_model = gr.Dropdown(["Erased Stable Diffusion(ESD)", "Forget-me-not(FMN)", "Ablating concepts(AC)","Unified Concept Editing(UCE)", "Safe Latent Diffusion(SLD)"], 
                                   label="Unlearned DMs")
        with gr.Column():
                # gr.Markdown("Please upload your model id.")
                drop_text = gr.Dropdown(["Object-Church", "Object-Parachute", "Object-Garbage_Truck","Object-Tench",
                                "Style-Van_Gogh","Concept-Nudity", "None"], 
                                   label="AdvUnlearn Text Encoder")
        
    with gr.Row() as attack:
        text_input = gr.Textbox(label="Prompt")
    with gr.Row():
        with gr.Column(min_width=260):
            img1 = gr.Image("images/cheetah.jpg",label="Image Generated without AdvUnlearn",width=260,show_share_button=False,show_download_button=False)
        with gr.Column():
            start_button = gr.Button("AdvUnlearn",size='lg')
        with gr.Column(min_width=260):
            img2 = gr.Image("images/cheetah.jpg",label="Image Generated with AdvUnlearn",width=260,show_share_button=False,show_download_button=False)
            
demo.launch()