File size: 12,749 Bytes
98d5ec0
016b059
98d5ec0
 
 
 
 
 
 
 
 
 
 
 
 
6742856
cb7718b
2531620
98d5ec0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2531620
98d5ec0
 
 
 
 
 
 
 
 
 
 
 
 
cb7718b
98d5ec0
 
 
 
 
 
 
cb7718b
98d5ec0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
cb7718b
53af573
 
 
98d5ec0
 
 
53af573
98d5ec0
 
 
 
 
 
3095dd5
98d5ec0
 
3095dd5
98d5ec0
 
 
 
 
 
 
 
 
 
3095dd5
98d5ec0
 
53af573
98d5ec0
 
 
 
 
 
53af573
98d5ec0
 
 
 
 
 
 
 
 
 
 
53af573
98d5ec0
 
 
 
 
 
 
 
 
 
8dc9c38
98d5ec0
 
8dc9c38
98d5ec0
 
 
 
 
 
 
 
 
53af573
 
 
98d5ec0
 
 
016b059
98d5ec0
bb174ab
 
98d5ec0
 
016b059
bb174ab
 
 
 
 
 
a27cdb1
98d5ec0
2531620
bb174ab
 
016b059
bb174ab
 
98d5ec0
3a35a16
016b059
bb174ab
 
98d5ec0
 
 
 
bb174ab
016b059
98d5ec0
 
 
53af573
bb174ab
98d5ec0
016b059
 
bb174ab
98d5ec0
 
 
bb174ab
 
 
c139d5c
 
98d5ec0
c139d5c
 
98d5ec0
bb174ab
98d5ec0
ba222f4
98d5ec0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bb174ab
 
98d5ec0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
dd5d6cc
 
98d5ec0
016b059
 
 
 
 
 
98d5ec0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
import os
import random
import numpy as np
import gradio as gr

# --- Hugging Face Spaces ๋ฐ์ฝ”๋ ˆ์ดํ„ฐ(์—†์–ด๋„ ๋™์ž‘ํ•˜๋„๋ก ๋Œ€์ฒด) ---
try:
    import spaces
    GPU_DECORATOR = spaces.GPU
except Exception:
    def GPU_DECORATOR(*args, **kwargs):
        def _wrap(fn):
            return fn
        return _wrap

import torch
from diffusers import DiffusionPipeline

# -----------------------
# ์žฅ์น˜/์ •๋ฐ€๋„ ์ž๋™ ์„ ํƒ
# -----------------------
def select_device_dtype():
    if torch.cuda.is_available():
        device = "cuda"
        dtype = torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float16
    else:
        device = "cpu"
        dtype = torch.float32
    return device, dtype

device, dtype = select_device_dtype()
if device == "cuda":
    torch.backends.cuda.matmul.allow_tf32 = True

# ์ œํ•œ๊ฐ’
MAX_SEED = np.iinfo(np.uint32).max
MAX_SIDE = 2048
MAX_TOTAL_PIXELS = 2_359_296  # ํ•ด์ƒ๋„ ์ด ํ”ฝ์…€ ๊ฐ€๋“œ(์•ฝ 2.36MP)

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

# -----------------------
# ์œ ํ‹ธ
# -----------------------
def _clamp_hw(width: int, height: int):
    width = int(max(256, min(int(width), MAX_SIDE)))
    height = int(max(256, min(int(height), MAX_SIDE)))
    if width * height > MAX_TOTAL_PIXELS:
        scale = (MAX_TOTAL_PIXELS / (width * height)) ** 0.5
        width = int((width * scale) // 32 * 32)
        height = int((height * scale) // 32 * 32)
        width = max(256, min(width, MAX_SIDE))
        height = max(256, min(height, MAX_SIDE))
    return width, height

def _validate_params(prompt: str, steps: int, guidance: float):
    if not prompt or not prompt.strip():
        raise ValueError("ํ”„๋กฌํ”„ํŠธ๊ฐ€ ๋น„์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ๋‚ด์šฉ์„ ์ž…๋ ฅํ•ด ์ฃผ์„ธ์š”.")
    if not (1 <= steps <= 50):
        raise ValueError("์ถ”๋ก  ์Šคํ…์€ 1~50 ๋ฒ”์œ„์—ฌ์•ผ ํ•ฉ๋‹ˆ๋‹ค.")
    if not (0.0 <= guidance <= 20.0):
        raise ValueError("๊ฐ€์ด๋˜์Šค ์Šค์ผ€์ผ์€ 0.0~20.0 ๋ฒ”์œ„์—ฌ์•ผ ํ•ฉ๋‹ˆ๋‹ค.")

# -----------------------
# ์ƒ์„ฑ ํ•จ์ˆ˜
# -----------------------
@GPU_DECORATOR()
def generate_image(prompt, seed, randomize_seed, width, height, steps, guidance_scale, progress=gr.Progress(track_tqdm=True)):
    try:
        prompt = prompt.strip()
        _validate_params(prompt, steps, guidance_scale)

        if randomize_seed:
            seed = random.randint(0, MAX_SEED)
        generator = torch.Generator(device=device).manual_seed(int(seed))

        width, height = _clamp_hw(width, height)

        progress(0.1, desc="์ดˆ๊ธฐํ™” ์ค‘โ€ฆ")
        if device == "cuda":
            autocast_ctx = torch.autocast(device_type="cuda", dtype=dtype)
        elif device == "cpu":
            autocast_ctx = torch.autocast(device_type="cpu", dtype=dtype) if dtype != torch.float32 else torch.no_grad()
        else:
            autocast_ctx = torch.no_grad()

        with autocast_ctx:
            progress(0.4, desc="์ด๋ฏธ์ง€ ์ƒ์„ฑ ์ค‘โ€ฆ")
            out = pipe(
                prompt=prompt,
                width=int(width),
                height=int(height),
                num_inference_steps=int(steps),
                generator=generator,
                guidance_scale=float(guidance_scale)
            )
            image = out.images[0]

        progress(1.0, desc="์™„๋ฃŒ")
        return image, int(seed)
    except Exception as e:
        gr.Error(f"์ƒ์„ฑ ์ค‘ ์˜ค๋ฅ˜: {type(e).__name__}: {e}")
        return None, int(seed)

def set_prompt(example_text):
    return example_text

# -----------------------
# ํ•œ๊ธ€ ์˜ˆ์‹œ ํ”„๋กฌํ”„ํŠธ
# -----------------------
example_prompts = {
    "์ œํ’ˆ ๋””์ž์ธ": [
        """์Šฌ๋ฆญํ•œ ์ธ๋”์ŠคํŠธ๋ฆฌ์–ผ ์Šคํƒ€์ผ์˜ ์ปคํ”ผ๋จธ์‹  ์ปจ์…‰ ์Šค์ผ€์น˜:
- ๊ณก์„ ํ˜• ๋ฉ”ํƒˆ ๋ฐ”๋””, ๋ฒ ์ ค ์ตœ์†Œํ™”
- ์„ค์ •์šฉ ํ„ฐ์น˜์Šคํฌ๋ฆฐ ํŒจ๋„
- ๋ชจ๋˜ํ•œ ๋งคํŠธ ๋ธ”๋ž™ ๋งˆ๊ฐ
- ์†๊ทธ๋ฆผ(์Šค์ผ€์น˜) ์ปจ์…‰ ์•„ํŠธ ์Šคํƒ€์ผ"""
    ],
    "๋งˆ์ธ๋“œ๋งต": [
        """์†๊ทธ๋ฆผ ์Šคํƒ€์ผ์˜ ๋‹ค์ฑ„๋กœ์šด ๋งˆ์ธ๋“œ๋งต, ๊ต์œก์šฉ, ์ƒ๋™๊ฐ ์žˆ๋Š” ์ƒ‰๊ฐ, ๋ช…ํ™•ํ•œ ๊ณ„์ธต ๊ตฌ์กฐ, ํ™ฉ๊ธˆ๋น„ ๋ ˆ์ด์•„์›ƒ.
KNOWLEDGE
โ”œโ”€โ”€ ACQUISITION [๋ฒˆ๊ฐœ๊ฐ€ ์นœ ๋‡Œ ~60px]
โ”‚   โ”œโ”€โ”€ READING [๋น›๋‚˜๋Š” ํŽผ์นœ ์ฑ…]
โ”‚   โ”œโ”€โ”€ PRACTICE [๊ณต๊ตฌ ์•„์ด์ฝ˜]
โ”‚   โ””โ”€โ”€ OBSERVATION [ํ™•๋Œ€๊ฒฝ ๋“  ๋ˆˆ]
โ”œโ”€โ”€ PROCESSING [๊ธฐ์–ด ๋„คํŠธ์›Œํฌ ~50px]
โ”‚   โ”œโ”€โ”€ ANALYSIS [์ƒ์Šน ๊ทธ๋ž˜ํ”„]
โ”‚   โ””โ”€โ”€ SYNTHESIS [ํผ์ฆ ์กฐ๊ฐ]
โ”œโ”€โ”€ RETENTION [๋ฉ”๋ชจ๋ฆฌ ์นฉ ~45px]
โ”‚   โ”œโ”€โ”€ SHORT-TERM [๋ฒˆ์ฉ์ž„]
โ”‚   โ””โ”€โ”€ LONG-TERM [๊ฒฌ๊ณ ํ•œ ์•„์นด์ด๋ธŒ]
โ””โ”€โ”€ APPLICATION
    โ”œโ”€โ”€ CREATION [ํŒ”๋ ˆํŠธ]
    โ””โ”€โ”€ INNOVATION [๋ณ„์ž๋ฆฌ ์ „๊ตฌ]"""
    ],
    "๋ชฉ์—…": [
        """์†๊ทธ๋ฆผ ์™€์ด์–ดํ”„๋ ˆ์ž„ ์Šคํƒ€์ผ์˜ ๋ชจ๋ฐ”์ผ ๋ฑ…ํ‚น ์•ฑ ๋ชฉ์—…:
- ๋กœ๊ณ ๊ฐ€ ์žˆ๋Š” ํƒ€์ดํ‹€ ํ™”๋ฉด
- ๋กœ๊ทธ์ธ(์•„์ด๋””, ๋น„๋ฐ€๋ฒˆํ˜ธ, ๋กœ๊ทธ์ธ ๋ฒ„ํŠผ)
- ๋Œ€์‹œ๋ณด๋“œ 3๊ฐœ ์„น์…˜(์ž”์•ก, ๊ฑฐ๋ž˜๋‚ด์—ญ, ๋น ๋ฅธ ์‹คํ–‰)
- ํ•˜๋‹จ ๋‚ด๋น„๊ฒŒ์ด์…˜(ํ™ˆ, ์ด์ฒด, ํ”„๋กœํ•„)"""
    ],
    "์ธํฌ๊ทธ๋ž˜ํ”ฝ": [
        """๋Œ€๊ธฐ์—… ์—ฐ์ฐจ๋ณด๊ณ ์„œ์šฉ ํ”Œ๋žซ ์Šคํƒ€์ผ ์ธํฌ๊ทธ๋ž˜ํ”ฝ:
- ์ œ๋ชฉ: "Global Renewable Energy Trends 2025"
- ๋ถ€์ œ: "์‹œ์žฅ์ ์œ ์œจ๊ณผ ์„ฑ์žฅ๋ถ„์„"
- ์‹œ๊ฐ ์š”์†Œ:
    - ์ง€์—ญ๋ณ„ ํƒœ์–‘๊ด‘ยทํ’๋ ฅยท์ˆ˜๋ ฅ ์ƒ์‚ฐ๋Ÿ‰ ๋ง‰๋Œ€๊ทธ๋ž˜ํ”„
    - ์—๋„ˆ์ง€ ๋น„์ค‘ ํŒŒ์ด์ฐจํŠธ: ํƒœ์–‘๊ด‘(45%)ยทํ’๋ ฅ(30%)ยท์ˆ˜๋ ฅ(25%)
    - ์—ฐ๋„๋ณ„ ์„ฑ์žฅ ์ถ”์„ธ์„ 
- ์•„์ด์ฝ˜: ๋ฏธ๋‹ˆ๋ฉ€ ํƒœ์–‘, ํ’๋ ฅ ํ„ฐ๋นˆ, ๋ฌผ๋ฐฉ์šธ
- ๋ ˆ์ด์•„์›ƒ: ๊ทธ๋ฆฌ๋“œ ๊ธฐ๋ฐ˜, ํŒŒ์Šคํ…” ํฌ์ธํŠธ, ํ™”์ดํŠธ ์ŠคํŽ˜์ด์Šค ์ถฉ๋ถ„
- ์ฃผ์„: KPI ํ•ต์‹ฌ ์ˆ˜์น˜ ๋ฐ ์ „๋ง ์ฝœ์•„์›ƒ"""
    ],
    "๋‹ค์ด์–ด๊ทธ๋žจ": [
        """์—”๋“œํˆฌ์—”๋“œ ๋น„์ฆˆ๋‹ˆ์Šค ์›Œํฌํ”Œ๋กœ ๋‹ค์ด์–ด๊ทธ๋žจ(์†๊ทธ๋ฆผ, ๊ต์œก์ ยท์ „๋ฌธ์ ):
- ์ œ๋ชฉ: "ํ†ตํ•ฉ ๋น„์ฆˆ๋‹ˆ์Šค ํ”„๋กœ์„ธ์Šค"
- ๊ตฌ์„ฑ:
    - ์‹œ์žฅ๋ถ„์„(์ฐจํŠธ, ๊ฒฝ์Ÿ์ž ๋งต)
    - ์ „๋žต์ˆ˜๋ฆฝ(๋ธŒ๋ ˆ์ธ์Šคํ† ๋ฐ ํด๋ผ์šฐ๋“œ, ํ•ต์‹ฌ ํฌ์ปค์Šค)
    - ์ œํ’ˆ์„ค๊ณ„(์Šค์ผ€์น˜, ํ”ผ๋“œ๋ฐฑ ๋ฃจํ”„)
    - ๊ตฌํ˜„(ํƒ€์ž„๋ผ์ธ ๋งˆ์ปค, ๋ฆฌ์†Œ์Šค ์•„์ด์ฝ˜)
    - ์ถœ์‹œ ํ›„ ๋ฆฌ๋ทฐ(์ง€ํ‘œ, ์ง€์† ๊ฐœ์„ )
- ๋ช…ํ™•ํ•œ ๋ฐฉํ–ฅ ํ™”์‚ดํ‘œ, ์ƒ‰์ƒ์œผ๋กœ ๋‹จ๊ณ„ ๊ตฌ๋ถ„"""
    ],
    "ํ”Œ๋กœ์šฐ์ฐจํŠธ": [
        """์†๊ทธ๋ฆผ ์Šคํƒ€์ผ ํ”Œ๋กœ์šฐ์ฐจํŠธ, ์„ ๋ช…ํ•œ ์ƒ‰, ๋ฏธ๋‹ˆ๋ฉ€ ์•„์ด์ฝ˜.
BUSINESS WORKFLOW
โ”œโ”€โ”€ ์‹œ์ž‘ [์ดˆ๋ก ๋ฒ„ํŠผ ~40px]
โ”‚   โ”œโ”€โ”€ ์š”๊ตฌ์‚ฌํ•ญ ์ˆ˜์ง‘ [ํด๋” ์•„์ด์ฝ˜]
โ”‚   โ””โ”€โ”€ ๋ฐ์ดํ„ฐ ๋ถ„์„ [์ฐจํŠธ ์•„์ด์ฝ˜]
โ”œโ”€โ”€ ๊ตฌํ˜„ [์ฝ”๋”ฉ ์‹ฌ๋ณผ ~50px]
โ”‚   โ”œโ”€โ”€ ํ”„๋ก ํŠธ์—”๋“œ [๋ธŒ๋ผ์šฐ์ € ์•„์ด์ฝ˜]
โ”‚   โ””โ”€โ”€ ๋ฐฑ์—”๋“œ [์„œ๋ฒ„ ์•„์ด์ฝ˜]
โ”œโ”€โ”€ ํ…Œ์ŠคํŠธ & ํ†ตํ•ฉ [๊ธฐ์–ด ์•„์ด์ฝ˜ ~45px]
โ””โ”€โ”€ ๋ฐฐํฌ
    โ””โ”€โ”€ ์ข…๋ฃŒ [์ฒด์ปค๊ธฐ ๊นƒ๋ฐœ ~40px]"""
    ]
}

# -----------------------
# Gradio UI (ํ•œ๊ตญ์–ด)
# -----------------------
css = """
* { box-sizing: border-box; }
body {
    background: linear-gradient(135deg, #667eea, #764ba2);
    font-family: 'Pretendard', 'Apple SD Gothic Neo', 'Noto Sans KR', 'Helvetica Neue', Arial, sans-serif;
    color: #333; margin: 0; padding: 0;
}
.gradio-container {
    background: rgba(255, 255, 255, 0.95);
    border-radius: 15px;
    padding: 30px 40px;
    box-shadow: 0 8px 30px rgba(0, 0, 0, 0.3);
    margin: 40px auto;
    width: 1200px;
    overflow: visible !important;
}
.sidebar {
    background: rgba(255, 255, 255, 0.98);
    border-radius: 10px;
    padding: 20px;
    box-shadow: 0 4px 15px rgba(0, 0, 0, 0.2);
    position: relative; z-index: 10;
    overflow: visible !important;
}
button, .btn {
    background: linear-gradient(90deg, #ff8a00, #e52e71);
    border: none; color: #fff;
    padding: 12px 24px; text-transform: uppercase;
    font-weight: bold; letter-spacing: 1px;
    border-radius: 5px; cursor: pointer;
    transition: transform 0.2s ease-in-out;
}
button:hover, .btn:hover { transform: scale(1.05); }
.example-accordion { width: 100% !important; max-width: 100% !important; }
.example-accordion button { width: auto !important; white-space: normal !important; }
"""

with gr.Blocks(css=css, title="์›Œํฌํ”Œ๋กœ ์บ”๋ฒ„์Šค") as demo:
    gr.Markdown(
        """
        <div style="text-align:center;">
            <h1>์›Œํฌํ”Œ๋กœ ์บ”๋ฒ„์Šค</h1>
            <p>์—ฌ๋Ÿฌ ํƒญ์—์„œ ๋น„์ฆˆ๋‹ˆ์Šค์— ํ•„์š”ํ•œ ๋””์ž์ธ ์ปจ์…‰๊ณผ ์›Œํฌํ”Œ๋กœ ๋‹ค์ด์–ด๊ทธ๋žจ์„ ์ƒ์„ฑํ•ด ๋ณด์„ธ์š”.</p>
            <p><strong>์ปค๋ฎค๋‹ˆํ‹ฐ:</strong> <a href="https://discord.gg/openfreeai" target="_blank">https://discord.gg/openfreeai</a></p>
        </div>
        """
    )
    gr.HTML(
        """<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fginigen-Workflow-Canvas.hf.space">
        <img src="https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fginigen-Workflow-Canvas.hf.space&countColor=%23263759" alt="๋ฐฉ๋ฌธ์ž ๋ฐฐ์ง€"/>
        </a>"""
    )

    with gr.Row():
        # ์™ผ์ชฝ ์‚ฌ์ด๋“œ๋ฐ”: ๊ณตํ†ต ํŒŒ๋ผ๋ฏธํ„ฐ
        with gr.Column(scale=2, elem_classes="sidebar"):
            gr.Markdown("### ์ƒ์„ฑ ํŒŒ๋ผ๋ฏธํ„ฐ")

            size_preset = gr.Dropdown(
                label="ํ•ด์ƒ๋„ ํ”„๋ฆฌ์…‹",
                choices=[
                    "1024x1024", "1536x1024", "1024x1536",
                    "1344x1344", "1536x1536", "1920x1080", "1080x1920"
                ],
                value="1024x1024"
            )
            width_slider = gr.Slider(label="๊ฐ€๋กœ ํ•ด์ƒ๋„(px)", minimum=256, maximum=MAX_SIDE, step=32, value=1024)
            height_slider = gr.Slider(label="์„ธ๋กœ ํ•ด์ƒ๋„(px)", minimum=256, maximum=MAX_SIDE, step=32, value=1024)

            def apply_preset(preset):
                w, h = map(int, preset.split("x"))
                w, h = _clamp_hw(w, h)
                return w, h
            size_preset.change(fn=apply_preset, inputs=size_preset, outputs=[width_slider, height_slider])

            seed_slider = gr.Slider(label="์‹œ๋“œ(Seed)", minimum=0, maximum=int(MAX_SEED), step=1, value=42)
            randomize_seed = gr.Checkbox(label="์‹œ๋“œ ๋žœ๋ค", value=True)

            def toggle_seed(disable):
                return gr.update(interactive=not disable)
            randomize_seed.change(fn=toggle_seed, inputs=randomize_seed, outputs=seed_slider)

            steps_slider = gr.Slider(label="์ถ”๋ก  ์Šคํ…", minimum=1, maximum=50, step=1, value=20)
            guidance_slider = gr.Slider(label="๊ฐ€์ด๋˜์Šค ์Šค์ผ€์ผ", minimum=0.0, maximum=20.0, step=0.5, value=7.5)

        # ๋ฉ”์ธ: ํƒญ UI
        with gr.Column(scale=8):
            with gr.Tabs():
                def build_tab(tab_title, ex_key, placeholder_text):
                    with gr.Tab(tab_title):
                        tb = gr.Textbox(
                            label=f"{tab_title} ํ”„๋กฌํ”„ํŠธ",
                            placeholder=placeholder_text,
                            lines=5,
                            value=example_prompts[ex_key][0]
                        )
                        btn = gr.Button(f"{tab_title} ์ƒ์„ฑ")
                        img = gr.Image(label=f"{tab_title} ๊ฒฐ๊ณผ", type="pil", value=None, height=512)
                        with gr.Accordion("์˜ˆ์‹œ ํ”„๋กฌํ”„ํŠธ", open=True, elem_classes="example-accordion"):
                            for ex in example_prompts[ex_key]:
                                gr.Button(ex, variant="secondary").click(
                                    fn=lambda ex=ex: set_prompt(ex),
                                    outputs=tb
                                )
                        btn.click(
                            fn=generate_image,
                            inputs=[tb, seed_slider, randomize_seed, width_slider, height_slider, steps_slider, guidance_slider],
                            outputs=[img, seed_slider]
                        )

                build_tab("์ œํ’ˆ ๋””์ž์ธ", "์ œํ’ˆ ๋””์ž์ธ", "์ œํ’ˆ ๋””์ž์ธ ์ปจ์…‰์„ ์ž…๋ ฅํ•˜์„ธ์š”โ€ฆ")
                build_tab("๋งˆ์ธ๋“œ๋งต", "๋งˆ์ธ๋“œ๋งต", "๋งˆ์ธ๋“œ๋งต ์„ค๋ช…์„ ์ž…๋ ฅํ•˜์„ธ์š”โ€ฆ")
                build_tab("๋ชฉ์—…", "๋ชฉ์—…", "์•ฑ/์›น ๋ชฉ์—… ์„ค๋ช…์„ ์ž…๋ ฅํ•˜์„ธ์š”โ€ฆ")
                build_tab("์ธํฌ๊ทธ๋ž˜ํ”ฝ", "์ธํฌ๊ทธ๋ž˜ํ”ฝ", "์ธํฌ๊ทธ๋ž˜ํ”ฝ ์„ค๋ช…์„ ์ž…๋ ฅํ•˜์„ธ์š”โ€ฆ")
                build_tab("๋‹ค์ด์–ด๊ทธ๋žจ", "๋‹ค์ด์–ด๊ทธ๋žจ", "๋‹ค์ด์–ด๊ทธ๋žจ ์„ค๋ช…์„ ์ž…๋ ฅํ•˜์„ธ์š”โ€ฆ")
                build_tab("ํ”Œ๋กœ์šฐ์ฐจํŠธ", "ํ”Œ๋กœ์šฐ์ฐจํŠธ", "ํ”Œ๋กœ์šฐ์ฐจํŠธ ์„ค๋ช…์„ ์ž…๋ ฅํ•˜์„ธ์š”โ€ฆ")

if __name__ == "__main__":
    demo.queue(concurrency_count=2, max_size=32)
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=False,
        show_error=True,
        debug=True
    )