File size: 13,126 Bytes
e673944
2473931
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bfc1d04
2473931
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
import spaces
import gradio as gr
import torch
from diffusers import ZImagePipeline
import os
from pathlib import Path

# Initialize the pipeline
print("Loading Z-Image Turbo model...")
pipe = ZImagePipeline.from_pretrained(
    "Tongyi-MAI/Z-Image-Turbo",
    torch_dtype=torch.bfloat16,
    low_cpu_mem_usage=False,
)

# Move to GPU if available
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe.to(device)

# Optional: Enable Flash Attention for better efficiency
try:
    pipe.transformer.set_attention_backend("flash")
    print("Flash Attention enabled")
except:
    print("Flash Attention not available, using default")

print("Model loaded successfully!")

@spaces.GPU()
def generate_image(
    prompt,
    negative_prompt,
    height,
    width,
    num_steps,
    seed,
    progress=gr.Progress(track_tqdm=True)
):
    """
    Generate an image using Z-Image Turbo model.
    
    Args:
        prompt: Text description of the desired image
        negative_prompt: What to avoid in the image
        height: Image height
        width: Image width
        num_steps: Number of inference steps
        seed: Random seed for reproducibility
    
    Returns:
        Generated PIL Image
    """
    if not prompt.strip():
        raise gr.Error("Please enter a prompt to generate an image.")
    
    # Set random seed for reproducibility
    generator = torch.Generator(device).manual_seed(int(seed))
    
    # Generate the image
    progress(0, desc="Initializing generation...")
    
    try:
        result = pipe(
            prompt=prompt,
            negative_prompt=negative_prompt if negative_prompt.strip() else None,
            height=int(height),
            width=int(width),
            num_inference_steps=int(num_steps),
            guidance_scale=0.0,  # Turbo models use 0 guidance
            generator=generator,
        )
        
        image = result.images[0]
        progress(1.0, desc="Complete!")
        
        return image
    
    except Exception as e:
        raise gr.Error(f"Generation failed: {str(e)}")

# Apple-inspired CSS
apple_css = """
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');

* {
    font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif !important;
}

.gradio-container {
    max-width: 1200px !important;
    margin: 0 auto !important;
    background: linear-gradient(135deg, #f5f7fa 0%, #e8ecf1 100%) !important;
}

.main-header {
    text-align: center;
    padding: 2.5rem 1rem 1.5rem 1rem;
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
    border-radius: 24px;
    margin-bottom: 2rem;
    box-shadow: 0 10px 40px rgba(102, 126, 234, 0.3);
}

.main-header h1 {
    font-size: 2.5rem !important;
    font-weight: 700 !important;
    color: white !important;
    margin: 0 0 0.5rem 0 !important;
    letter-spacing: -0.5px;
}

.main-header p {
    font-size: 1.1rem !important;
    color: rgba(255, 255, 255, 0.9) !important;
    margin: 0 !important;
    font-weight: 400;
}

.attribution {
    text-align: center;
    margin-top: 0.5rem;
    font-size: 0.9rem;
    color: rgba(255, 255, 255, 0.8);
}

.attribution a {
    color: white !important;
    text-decoration: none;
    font-weight: 600;
    transition: opacity 0.2s;
}

.attribution a:hover {
    opacity: 0.8;
}

.control-panel {
    background: white;
    border-radius: 20px;
    padding: 1.5rem;
    box-shadow: 0 4px 20px rgba(0, 0, 0, 0.08);
    margin-bottom: 1.5rem;
}

.output-panel {
    background: white;
    border-radius: 20px;
    padding: 1.5rem;
    box-shadow: 0 4px 20px rgba(0, 0, 0, 0.08);
    min-height: 600px;
}

.primary-btn {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
    border: none !important;
    border-radius: 12px !important;
    padding: 0.875rem 2rem !important;
    font-size: 1rem !important;
    font-weight: 600 !important;
    color: white !important;
    transition: all 0.3s ease !important;
    box-shadow: 0 4px 15px rgba(102, 126, 234, 0.3) !important;
}

.primary-btn:hover {
    transform: translateY(-2px) !important;
    box-shadow: 0 6px 20px rgba(102, 126, 234, 0.4) !important;
}

.secondary-btn {
    background: #f3f4f6 !important;
    border: 1px solid #e5e7eb !important;
    border-radius: 12px !important;
    padding: 0.875rem 2rem !important;
    font-size: 1rem !important;
    font-weight: 500 !important;
    color: #374151 !important;
    transition: all 0.3s ease !important;
}

.secondary-btn:hover {
    background: #e5e7eb !important;
    transform: translateY(-1px) !important;
}

textarea, input, .input-container {
    border-radius: 12px !important;
    border: 1.5px solid #e5e7eb !important;
    transition: all 0.2s ease !important;
    font-size: 0.95rem !important;
}

textarea:focus, input:focus {
    border-color: #667eea !important;
    box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1) !important;
}

.slider-container input[type="range"] {
    accent-color: #667eea !important;
}

label {
    font-weight: 600 !important;
    color: #1f2937 !important;
    font-size: 0.9rem !important;
    margin-bottom: 0.5rem !important;
}

.example-card {
    border-radius: 12px !important;
    transition: all 0.3s ease !important;
    cursor: pointer !important;
    border: 2px solid transparent !important;
}

.example-card:hover {
    border-color: #667eea !important;
    transform: scale(1.02) !important;
}

.accordion {
    border-radius: 12px !important;
    border: 1.5px solid #e5e7eb !important;
    overflow: hidden !important;
}

#output-image {
    border-radius: 16px !important;
    overflow: hidden !important;
}

.footer-note {
    text-align: center;
    padding: 1.5rem;
    color: #6b7280;
    font-size: 0.9rem;
    margin-top: 2rem;
}

@media (max-width: 768px) {
    .main-header h1 {
        font-size: 1.75rem !important;
    }
    
    .main-header p {
        font-size: 0.95rem !important;
    }
    
    .control-panel, .output-panel {
        padding: 1rem;
    }
}
"""

# Example prompts
examples = [
    [
        "Young Chinese woman in red Hanfu, intricate embroidery. Impeccable makeup, red floral forehead pattern. Elaborate high bun, golden phoenix headdress, red flowers, beads. Holds round folding fan with lady, trees, bird. Neon lightning-bolt lamp (⚡️), bright yellow glow, above extended left palm. Soft-lit outdoor night background, silhouetted tiered pagoda (西安大雁塔), blurred colorful distant lights.",
        "",
        1024,
        1024,
        9,
        42
    ],
    [
        "A serene Japanese garden with cherry blossoms in full bloom, koi pond with crystal clear water, traditional wooden bridge, soft morning light filtering through trees, ultra detailed, photorealistic",
        "blurry, low quality, distorted",
        1024,
        1024,
        9,
        123
    ],
    [
        "Futuristic cyberpunk city at night, neon signs reflecting on wet streets, flying cars, towering skyscrapers with holographic advertisements, rain, cinematic lighting, highly detailed",
        "daytime, bright, low quality",
        1024,
        1024,
        9,
        456
    ],
    [
        "Majestic dragon soaring through clouds at sunset, scales shimmering with iridescent colors, mountains in background, fantasy art style, epic composition, dramatic lighting",
        "cartoon, simple, flat",
        1024,
        1024,
        9,
        789
    ],
    [
        "Cozy coffee shop interior, warm lighting, wooden furniture, plants on shelves, barista preparing coffee, steam rising from cup, bokeh background, inviting atmosphere",
        "empty, cold, harsh lighting",
        1024,
        1024,
        9,
        321
    ]
]

# Create the Gradio interface
with gr.Blocks(
    theme=gr.themes.Soft(
        primary_hue="violet",
        secondary_hue="purple",
        neutral_hue="slate",
        font=gr.themes.GoogleFont("Inter")
    ),
    css=apple_css,
    title="Z-Image Turbo - AI Image Generator",
    fill_height=False
) as demo:
    
    # Header
    with gr.Row():
        with gr.Column():
            gr.HTML("""
                <div class="main-header">
                    <h1>✨ Z-Image Turbo</h1>
                    <p>Create stunning images from text in seconds</p>
                    <div class="attribution">
                        Built with <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank">anycoder</a>
                    </div>
                </div>
            """)
    
    with gr.Row():
        # Left column - Controls
        with gr.Column(scale=1, elem_classes="control-panel"):
            prompt = gr.Textbox(
                label="✍️ Prompt",
                placeholder="Describe the image you want to create...",
                lines=4,
                max_lines=8
            )
            
            negative_prompt = gr.Textbox(
                label="🚫 Negative Prompt (Optional)",
                placeholder="What you don't want in the image...",
                lines=2,
                max_lines=4
            )
            
            with gr.Accordion("⚙️ Advanced Settings", open=False, elem_classes="accordion"):
                with gr.Row():
                    width = gr.Slider(
                        minimum=512,
                        maximum=2048,
                        value=1024,
                        step=64,
                        label="Width",
                        elem_classes="slider-container"
                    )
                    height = gr.Slider(
                        minimum=512,
                        maximum=2048,
                        value=1024,
                        step=64,
                        label="Height",
                        elem_classes="slider-container"
                    )
                
                num_steps = gr.Slider(
                    minimum=4,
                    maximum=20,
                    value=9,
                    step=1,
                    label="Inference Steps",
                    info="More steps = better quality but slower",
                    elem_classes="slider-container"
                )
                
                seed = gr.Number(
                    label="Seed",
                    value=42,
                    precision=0,
                    info="Use same seed for reproducible results"
                )
                
                random_seed_btn = gr.Button(
                    "🎲 Random Seed",
                    elem_classes="secondary-btn",
                    size="sm"
                )
            
            with gr.Row():
                generate_btn = gr.Button(
                    "🎨 Generate Image",
                    variant="primary",
                    elem_classes="primary-btn",
                    size="lg"
                )
                clear_btn = gr.ClearButton(
                    [prompt, negative_prompt],
                    value="🗑️ Clear",
                    elem_classes="secondary-btn",
                    size="lg"
                )
        
        # Right column - Output
        with gr.Column(scale=1, elem_classes="output-panel"):
            output_image = gr.Image(
                label="Generated Image",
                type="pil",
                elem_id="output-image",
                show_label=False,
                show_download_button=True,
                show_share_button=True,
                height=600
            )
    
    # Examples section
    with gr.Row():
        gr.Examples(
            examples=examples,
            inputs=[prompt, negative_prompt, height, width, num_steps, seed],
            outputs=output_image,
            fn=generate_image,
            cache_examples=False,
            label="💡 Try these examples",
            examples_per_page=5,
            elem_classes="example-card"
        )
    
    # Footer
    gr.HTML("""
        <div class="footer-note">
            <p>Powered by <strong>Z-Image Turbo</strong> from Tongyi-MAI | 
            Optimized for fast, high-quality image generation</p>
            <p style="margin-top: 0.5rem; font-size: 0.85rem;">
                💡 Tip: Be specific and detailed in your prompts for best results
            </p>
        </div>
    """)
    
    # Event handlers
    def randomize_seed():
        import random
        return random.randint(0, 2**32 - 1)
    
    random_seed_btn.click(
        fn=randomize_seed,
        inputs=[],
        outputs=seed
    )
    
    generate_btn.click(
        fn=generate_image,
        inputs=[prompt, negative_prompt, height, width, num_steps, seed],
        outputs=output_image,
        api_name="generate"
    )
    
    # Also allow generation on Enter key in prompt
    prompt.submit(
        fn=generate_image,
        inputs=[prompt, negative_prompt, height, width, num_steps, seed],
        outputs=output_image
    )

# Launch the app
if __name__ == "__main__":
    demo.launch(
        share=False,
        show_error=True,
        favicon_path=None
    )