import os
import gradio as gr
import torch
import numpy as np
import random
from diffusers import FluxPipeline, FluxTransformer2DModel
import spaces
from translatepy import Translator

# 환경 변수 설정
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
translator = Translator()
HF_TOKEN = os.environ.get("HF_TOKEN", None)

# 상수
model = "black-forest-labs/FLUX.1-dev"
MAX_SEED = np.iinfo(np.int32).max

# CSS 및 JS 설정
CSS = """
footer {
    visibility: hidden;
}
"""

JS = """function () {
  gradioURL = window.location.href
  if (!gradioURL.endsWith('?__theme=dark')) {
    window.location.replace(gradioURL + '?__theme=dark');
  }
}"""

# Initialize `pipe` to None globally
pipe = None

# 모델 로드 시도
try:
    transformer = FluxTransformer2DModel.from_pretrained("sayakpaul/FLUX.1-merged", torch_dtype=torch.bfloat16)
    if torch.cuda.is_available():
        pipe = FluxPipeline.from_pretrained(
            model,
            transformer=transformer,
            torch_dtype=torch.bfloat16).to("cuda")
    else:
        print("CUDA is not available. Check your GPU settings.")
except Exception as e:
    print(f"Failed to load the model: {e}")

# 이미지 생성 함수
def generate_image(prompt, width=1024, height=1024, scales=5, steps=4, seed=-1, nums=1, progress=gr.Progress(track_tqdm=True)):
    if pipe is None:
        print("Model is not loaded properly. Please check the logs for details.")
        return None, "Model not loaded."

    if seed == -1:
        seed = random.randint(0, MAX_SEED)
    seed = int(seed)
    text = str(translator.translate(prompt, 'English'))
    generator = torch.Generator().manual_seed(seed)

    try:
        images = pipe(prompt=text, height=height, width=width, guidance_scale=scales, num_inference_steps=steps, max_sequence_length=512, num_images_per_prompt=nums, generator=generator).images
    except Exception as e:
        print(f"Error generating image: {e}")
        return None, "Error during image generation."

    return images, seed

# Gradio 인터페이스 구성 및 실행
with gr.Blocks(css=CSS, js=JS, theme="soft") as demo:
    gr.HTML("<h1><center>Flux Labs</center></h1>")
    gr.HTML("<p><center>Model Now: <a href='https://huggingface.co/sayakpaul/FLUX.1-merged'>FLUX.1 Merged</a><br>🙇‍♂️Frequent model changes</center></p>")
    with gr.Row():
        with gr.Column(scale=4):
            img = gr.Gallery(label='flux Generated Image', columns=1, preview=True, height=600)
            prompt = gr.Textbox(label='Enter Your Prompt (Multi-Languages)', placeholder="Enter prompt...", scale=6)
            sendBtn = gr.Button(scale=1, variant='primary')
        with gr.Accordion("Advanced Options", open=True):
            width = gr.Slider(label="Width", minimum=512, maximum=1280, step=8, value=1024)
            height = gr.Slider(label="Height", minimum=512, maximum=1280, step=8, value=1024)
            scales = gr.Slider(label="Guidance", minimum=3.5, maximum=7, step=0.1, value=3.5)
            steps = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=4)
            seed = gr.Slider(label="Seeds", minimum=-1, maximum=MAX_SEED, step=1, value=0)
            nums = gr.Slider(label="Image Numbers", minimum=1, maximum=4, step=1, value=1)
    sendBtn.click(fn=generate_image, inputs=[prompt, width, height, scales, steps, seed, nums], outputs=[img, seed])
    prompt.submit(fn=generate_image, inputs=[prompt, width, height, scales, steps, seed, nums], outputs=[img, seed])

demo.queue().launch()