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Upload folder using huggingface_hub

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  1. app.py +17 -28
app.py CHANGED
@@ -340,7 +340,6 @@ example_prompts = [
340
  "A sleek, futuristic sports car with glowing blue accents, racing through a virtual reality landscape, 3D render",
341
  ]
342
 
343
-
344
  # Use a state variable to store session ID
345
  with gr.Blocks(theme=gr.themes.Soft()) as demo:
346
  session_id = gr.State(None) # Add this to store session ID
@@ -348,25 +347,19 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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  gr.Markdown("# 🌊 WaveSpeed AI HiDream Arena")
349
 
350
  # Add the introduction with link to WaveSpeedAI
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- gr.Markdown(
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- """
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  [WaveSpeedAI](https://wavespeed.ai/) is the global pioneer in accelerating AI-powered video and image generation.
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  "Our in-house inference accelerator provides lossless speedup on image & video generation based on our rich inference optimization software stack, including our in-house inference compiler, CUDA kernel libraries and parallel computing libraries."
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- """
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- )
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- gr.Markdown(
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- """
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  This demo showcases the performance and outputs of leading image generation models, including HiDream and Flux, on our accelerated inference platform.
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- """
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- )
362
 
363
  with gr.Row():
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  with gr.Column(scale=3):
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- example_dropdown = gr.Dropdown(
366
- choices=example_prompts,
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- label="Choose an example prompt",
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- interactive=True
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- )
370
  input_text = gr.Textbox(
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  example_prompts[0],
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  label="Enter your prompt",
@@ -376,7 +369,9 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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  with gr.Column(scale=1):
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  generate_btn = gr.Button("Generate", variant="primary")
378
 
379
- example_dropdown.change(lambda ex: ex, inputs=[example_dropdown], outputs=[input_text])
 
 
380
 
381
  # Two status boxes - small (default) and big (during generation)
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  small_status_box = gr.Markdown("Ready to generate images",
@@ -400,13 +395,10 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
400
  performance_plot = gr.Plot(label="Performance Metrics")
401
 
402
  with gr.Accordion("Recent Generations (last 8)", open=False):
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- recent_gallery = gr.Gallery(
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- label="Recent Generations",
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- show_label=False,
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- elem_id="recent-gallery",
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- columns=4,
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- height="auto",
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- ).style(grid=2)
410
 
411
  def update_recent_gallery(prompt, results):
412
  recent_generations.append({
@@ -417,15 +409,12 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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  })
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  if len(recent_generations) > 8:
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  recent_generations.pop(0)
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-
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  # Flatten the images from each generation
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  all_images = []
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  for gen in reversed(recent_generations): # Show newest first
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- all_images.extend([
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- gen["flux-dev"],
426
- gen["hidream-dev"],
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- gen["hidream-full"]
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- ])
429
 
430
  # Update the Gradio gallery with the new list
431
  return recent_gallery.update(value=all_images)
 
340
  "A sleek, futuristic sports car with glowing blue accents, racing through a virtual reality landscape, 3D render",
341
  ]
342
 
 
343
  # Use a state variable to store session ID
344
  with gr.Blocks(theme=gr.themes.Soft()) as demo:
345
  session_id = gr.State(None) # Add this to store session ID
 
347
  gr.Markdown("# 🌊 WaveSpeed AI HiDream Arena")
348
 
349
  # Add the introduction with link to WaveSpeedAI
350
+ gr.Markdown("""
 
351
  [WaveSpeedAI](https://wavespeed.ai/) is the global pioneer in accelerating AI-powered video and image generation.
352
  "Our in-house inference accelerator provides lossless speedup on image & video generation based on our rich inference optimization software stack, including our in-house inference compiler, CUDA kernel libraries and parallel computing libraries."
353
+ """)
354
+ gr.Markdown("""
 
 
355
  This demo showcases the performance and outputs of leading image generation models, including HiDream and Flux, on our accelerated inference platform.
356
+ """)
 
357
 
358
  with gr.Row():
359
  with gr.Column(scale=3):
360
+ example_dropdown = gr.Dropdown(choices=example_prompts,
361
+ label="Choose an example prompt",
362
+ interactive=True)
 
 
363
  input_text = gr.Textbox(
364
  example_prompts[0],
365
  label="Enter your prompt",
 
369
  with gr.Column(scale=1):
370
  generate_btn = gr.Button("Generate", variant="primary")
371
 
372
+ example_dropdown.change(lambda ex: ex,
373
+ inputs=[example_dropdown],
374
+ outputs=[input_text])
375
 
376
  # Two status boxes - small (default) and big (during generation)
377
  small_status_box = gr.Markdown("Ready to generate images",
 
395
  performance_plot = gr.Plot(label="Performance Metrics")
396
 
397
  with gr.Accordion("Recent Generations (last 8)", open=False):
398
+ recent_gallery = gr.Gallery(label="Recent Generations",
399
+ columns=3,
400
+ rows=1,
401
+ show_label=True)
 
 
 
402
 
403
  def update_recent_gallery(prompt, results):
404
  recent_generations.append({
 
409
  })
410
  if len(recent_generations) > 8:
411
  recent_generations.pop(0)
412
+
413
  # Flatten the images from each generation
414
  all_images = []
415
  for gen in reversed(recent_generations): # Show newest first
416
+ all_images.extend(
417
+ [gen["flux-dev"], gen["hidream-dev"], gen["hidream-full"]])
 
 
 
418
 
419
  # Update the Gradio gallery with the new list
420
  return recent_gallery.update(value=all_images)