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import gradio as gr
import numpy as np
import random
import torch
from diffusers import DiffusionPipeline
import spaces
from transformers import pipeline

# ๊ธฐ๋ณธ ์„ค์ •
dtype = torch.bfloat16
device = "cuda" if torch.cuda.is_available() else "cpu"

# ํ•œ๊ตญ์–ด-์˜์–ด ๋ฒˆ์—ญ ๋ชจ๋ธ ๋กœ๋“œ (CPU์—์„œ ์‹คํ–‰)
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en", device="cpu")

# ๋ชจ๋ธ ๋กœ๋“œ
pipe = DiffusionPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-schnell",
    torch_dtype=dtype
).to(device)

MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 2048

# ์ œํ’ˆ ๋””์ž์ธ ์ปจ์…‰ ์˜ˆ์‹œ
EXAMPLES = [
    {
        "title": "Smart Coffee Machine",
        "prompt": """A sleek industrial design concept for a coffee machine:
        - Curved metallic body with minimal bezel
        - Touchscreen panel for settings
        - Modern matte black finish
        - Hand-drawn concept sketch style""",
        "width": 1024,
        "height": 1024
    },
    {
        "title": "AI Speaker",
        "prompt": """A futuristic AI speaker concept:
        - Cylindrical shape with LED ring near top
        - Voice assistant concept, floating panel controls
        - Smooth glossy finish with minimal seams
        - Techy, modern look in grayscale""",
        "width": 1024,
        "height": 1024
    },
    {
        "title": "Next-Gen Smartphone",
        "prompt": """A wireframe-style concept for a bezel-less smartphone:
        - Edge-to-edge display
        - Integrated camera under screen
        - Metallic frame, minimal ports
        - Sleek, glossy black design""",
        "width": 1024,
        "height": 1024
    },
    {
        "title": "Futuristic Electric Bicycle",
        "prompt": """An industrial design sketch of an electric bike:
        - Lightweight carbon frame, aerodynamic lines
        - Integrated battery, sleek display on handlebars
        - Neon color highlights on wheels
        - High-tech vibe, minimal clutter""",
        "width": 1024,
        "height": 1024
    },
    {
        "title": "Concept Car Interior",
        "prompt": """A luxurious and futuristic car interior concept:
        - Wrap-around digital dashboard
        - Minimalistic steering control, seat controls on touchscreen
        - Ambient LED accent lights
        - Soft leather seats, bright accent stitching""",
        "width": 1024,
        "height": 1024
    }
]

# Convert examples to Gradio format (if needed)
GRADIO_EXAMPLES = [
    [example["prompt"], example["width"], example["height"]]
    for example in EXAMPLES
]

# ํ•œ๊ตญ์–ด ๊ฐ์ง€ ํ•จ์ˆ˜
def contains_korean(text):
    for char in text:
        if ord('๊ฐ€') <= ord(char) <= ord('ํžฃ'):
            return True
    return False

# ํ•„์š”์‹œ ๋ฒˆ์—ญ ํ›„ ์ถ”๋ก  ํ•จ์ˆ˜
@spaces.GPU()
def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
    # ํ•œ๊ตญ์–ด ๊ฐ์ง€ ๋ฐ ๋ฒˆ์—ญ
    original_prompt = prompt
    translated = False
    
    if contains_korean(prompt):
        translated = True
        translation = translator(prompt)
        prompt = translation[0]['translation_text']
    
    # ๋žœ๋ค ์‹œ๋“œ ์„ค์ •
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    
    generator = torch.Generator().manual_seed(seed)
    
    # ๋ชจ๋ธ ์‹คํ–‰
    image = pipe(
        prompt=prompt,
        width=width,
        height=height,
        num_inference_steps=num_inference_steps,
        generator=generator,
        guidance_scale=0.0
    ).images[0]
    
    # ๋ฒˆ์—ญ ์ •๋ณด ๋ฐ˜ํ™˜
    if translated:
        return image, seed, original_prompt, prompt
    else:
        return image, seed, None, None

# CSS ์Šคํƒ€์ผ (๊ธฐ์กด ๊ตฌ์กฐ ์œ ์ง€)
css = """
.container {
    display: flex;
    flex-direction: row;
    height: 100%;
}
.input-column {
    flex: 1;
    padding: 20px;
    border-right: 2px solid #eee;
    max-width: 800px;
}
.examples-column {
    flex: 1;
    padding: 20px;
    overflow-y: auto;
    background: #f7f7f7;
}
.title {
    text-align: center;
    color: #2a2a2a;
    padding: 20px;
    font-size: 2.5em;
    font-weight: bold;
    background: linear-gradient(90deg, #f0f0f0 0%, #ffffff 100%);
    border-bottom: 3px solid #ddd;
    margin-bottom: 30px;
}
.subtitle {
    text-align: center;
    color: #666;
    margin-bottom: 30px;
}
.input-box {
    background: white;
    padding: 20px;
    border-radius: 10px;
    box-shadow: 0 2px 10px rgba(0,0,0,0.1);
    margin-bottom: 20px;
    width: 100%;
}
.input-box textarea {
    width: 100% !important;
    min-width: 600px !important;
    font-size: 14px !important;
    line-height: 1.5 !important;
    padding: 12px !important;
}
.example-card {
    background: white;
    padding: 15px;
    margin: 10px 0;
    border-radius: 8px;
    box-shadow: 0 2px 5px rgba(0,0,0,0.05);
}
.example-title {
    font-weight: bold;
    color: #2a2a2a;
    margin-bottom: 10px;
}
.contain {
    max-width: 1400px !important;
    margin: 0 auto !important;
}
.input-area {
    flex: 2 !important;
}
.examples-area {
    flex: 1 !important;
}
.translation-info {
    background-color: #f8f9fa;
    border-left: 4px solid #17a2b8;
    padding: 10px 15px;
    margin-top: 10px;
    border-radius: 4px;
    font-size: 14px;
}
"""

with gr.Blocks(css=css) as demo:
    gr.Markdown(
        """
        <div class="title">GINI Design</div>
        <div class="subtitle">Generate sleek industrial/product design concepts with FLUX AI</div>
        """)

    with gr.Row(equal_height=True):
        # ์™ผ์ชฝ ์ž…๋ ฅ ์ปฌ๋Ÿผ
        with gr.Column(elem_id="input-column", scale=2):
            with gr.Group(elem_classes="input-box"):
                prompt = gr.Text(
                    label="Design Prompt (ํ•œ๊ตญ์–ด ๋˜๋Š” ์˜์–ด๋กœ ์ž…๋ ฅํ•˜์„ธ์š”)",
                    placeholder="Enter your product design concept details in Korean or English...",
                    lines=10,
                    elem_classes="prompt-input"
                )
                run_button = gr.Button("Generate Design", variant="primary")
                result = gr.Image(label="Generated Design")
                
                # ๋ฒˆ์—ญ ์ •๋ณด ํ‘œ์‹œ ์˜์—ญ
                original_prompt = gr.Textbox(visible=False)
                translated_prompt = gr.Textbox(visible=False)
                translation_info = gr.Markdown(visible=False, elem_classes="translation-info")
                
                # ๋ฒˆ์—ญ ์ •๋ณด ์—…๋ฐ์ดํŠธ ํ•จ์ˆ˜
                def update_translation_info(original, translated):
                    if original and translated:
                        return gr.update(visible=True, value=f"๐Ÿ”„ Korean prompt was translated to English:\n\n**Original:** {original}\n\n**Translated:** {translated}")
                    else:
                        return gr.update(visible=False)
            
            with gr.Accordion("Advanced Settings", open=False):
                seed = gr.Slider(
                    label="Seed",
                    minimum=0,
                    maximum=MAX_SEED,
                    step=1,
                    value=0,
                )
                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
                
                with gr.Row():
                    width = gr.Slider(
                        label="Width",
                        minimum=256,
                        maximum=MAX_IMAGE_SIZE,
                        step=32,
                        value=1024,
                    )
                    height = gr.Slider(
                        label="Height",
                        minimum=256,
                        maximum=MAX_IMAGE_SIZE,
                        step=32,
                        value=1024,
                    )
                
                num_inference_steps = gr.Slider(
                    label="Number of inference steps",
                    minimum=1,
                    maximum=50,
                    step=1,
                    value=4,
                )
        
        # ์˜ค๋ฅธ์ชฝ ์˜ˆ์ œ ์ปฌ๋Ÿผ
        with gr.Column(elem_id="examples-column", scale=1):
            gr.Markdown("### Example Product Designs")
            for example in EXAMPLES:
                with gr.Group(elem_classes="example-card"):
                    gr.Markdown(f"#### {example['title']}")
                    gr.Markdown(f"```\n{example['prompt']}\n```")
                    
                    def create_example_handler(ex):
                        def handler():
                            return {
                                prompt: ex["prompt"],
                                width: ex["width"],
                                height: ex["height"]
                            }
                        return handler
                    
                    gr.Button("Use This Example", size="sm").click(
                        fn=create_example_handler(example),
                        outputs=[prompt, width, height]
                    )

    # ์ด๋ฒคํŠธ ๋ฐ”์ธ๋”ฉ (๋ฒ„ํŠผ ํด๋ฆญ & ํ…์ŠคํŠธ๋ฐ•์Šค ์—”ํ„ฐ)
    gr.on(
        triggers=[run_button.click, prompt.submit],
        fn=infer,
        inputs=[prompt, seed, randomize_seed, width, height, num_inference_steps],
        outputs=[result, seed, original_prompt, translated_prompt]
    )
    
    # ๋ฒˆ์—ญ ์ •๋ณด ์—…๋ฐ์ดํŠธ ์ด๋ฒคํŠธ
    gr.on(
        triggers=[original_prompt.change, translated_prompt.change],
        fn=update_translation_info,
        inputs=[original_prompt, translated_prompt],
        outputs=[translation_info]
    )

if __name__ == "__main__":
    demo.queue()
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        show_error=True,
        debug=True
    )