import os
import random
import uuid
import json
import gradio as gri
import numpy as np
from PIL import Image
import spaces
import torch
from fooocus import FooocusPipeline
from typing import Tuple

# Check for the Model Base..// (Commented out line)

bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
default_negative = os.getenv("default_negative", "")

def check_text(prompt, negative=""):
  for i in bad_words:
    if i in prompt:
      return True
  for i in bad_words_negative:
    if i in negative:
      return True
  return False


style_list = [
    {
        "name": "2560 x 1440",
        "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
    },
    {
        "name": "Photo",
        "prompt": "cinematic photo {prompt}. 35mm photograph, film, bokeh, professional, 4k, highly detailed",
        "negative_prompt": "drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly",
    },
    {
        "name": "Cinematic",
        "prompt": "cinematic still {prompt}. emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
        "negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
    },
    {
        "name": "Anime",
        "prompt": "anime artwork {prompt}. anime style, key visual, vibrant, studio anime, highly detailed",
        "negative_prompt": "photo, deformed, black and white, realism, disfigured, low contrast",
    },
    {
        "name": "3D Model",
        "prompt": "professional 3d model {prompt}. octane render, highly detailed, volumetric, dramatic lighting",
        "negative_prompt": "ugly, deformed, noisy, low poly, blurry, painting",
    },
    {
        "name": "(No style)",
        "prompt": "{prompt}",
        "negative_prompt": "",
    },
]

styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
STYLE_NAMES = list(styles.keys())
DEFAULT_STYLE_NAME = "2560 x 1440"

def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
  p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
  if not negative:
      negative = ""
  return p.replace("{prompt}", positive), n + negative


DESCRIPTION = """## MidJourneyHepzeka.com Ücretsiz ve Sınırsız Görsel Üretmek için Yapay Zeka Modeli"""


if not torch.cuda.is_available():
    DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"

MAX_SEED = np.iinfo(np.int32).max
CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
NUM_IMAGES_PER_PROMPT = 1

if torch.cuda.is_available():
    pipe = FooocusPipeline.from_pretrained(
        "SG161222/RealVisXL_V3.0_Turbo",