import torch
import gradio as gr
from gradio import processing_utils, utils
from gradio_depth_pred import create_demo as create_depth_pred_demo
from PIL import Image
import random
from diffusers import (
    DiffusionPipeline,
    AutoencoderKL,
    StableDiffusionControlNetPipeline,
    ControlNetModel,
    StableDiffusionLatentUpscalePipeline,
    StableDiffusionImg2ImgPipeline,
    StableDiffusionControlNetImg2ImgPipeline,
    DPMSolverMultistepScheduler,  # <-- Added import
    EulerDiscreteScheduler  # <-- Added import
)

print(f"Is CUDA available: {torch.cuda.is_available()}")
print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'

import time
from style import css

BASE_MODEL = "SG161222/Realistic_Vision_V5.1_noVAE"

title = "Ultra Heroes"
description = "Testing composites and lighting tweaks."

def inference(text):
  output_flan = ""
  output_vanilla = ""
  return [output_flan, output_vanilla]

io = gr.Interface(
  inference,
  gr.Textbox(lines=3),
  outputs=[
    gr.Textbox(lines=3, label="Flan T5"),
    gr.Textbox(lines=3, label="T5")
  ],
  title=title,
  description=description,
)
io.launch()