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app.py
CHANGED
@@ -340,7 +340,6 @@ example_prompts = [
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"A sleek, futuristic sports car with glowing blue accents, racing through a virtual reality landscape, 3D render",
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]
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-
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# Use a state variable to store session ID
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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session_id = gr.State(None) # Add this to store session ID
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@@ -348,25 +347,19 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("# 🌊 WaveSpeed AI HiDream Arena")
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# 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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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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)
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with gr.Row():
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with gr.Column(scale=3):
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example_dropdown = gr.Dropdown(
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interactive=True
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)
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input_text = gr.Textbox(
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example_prompts[0],
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label="Enter your prompt",
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@@ -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")
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example_dropdown.change(lambda ex: ex,
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# Two status boxes - small (default) and big (during generation)
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small_status_box = gr.Markdown("Ready to generate images",
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@@ -400,13 +395,10 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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performance_plot = gr.Plot(label="Performance Metrics")
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with gr.Accordion("Recent Generations (last 8)", open=False):
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recent_gallery = gr.Gallery(
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columns=4,
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height="auto",
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).style(grid=2)
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def update_recent_gallery(prompt, results):
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recent_generations.append({
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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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# 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"],
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gen["hidream-dev"],
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gen["hidream-full"]
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])
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# Update the Gradio gallery with the new list
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return recent_gallery.update(value=all_images)
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"A sleek, futuristic sports car with glowing blue accents, racing through a virtual reality landscape, 3D render",
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]
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# Use a state variable to store session ID
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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session_id = gr.State(None) # Add this to store session ID
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gr.Markdown("# 🌊 WaveSpeed AI HiDream Arena")
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# Add the introduction with link to WaveSpeedAI
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gr.Markdown("""
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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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gr.Markdown("""
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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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with gr.Row():
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with gr.Column(scale=3):
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example_dropdown = gr.Dropdown(choices=example_prompts,
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label="Choose an example prompt",
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interactive=True)
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input_text = gr.Textbox(
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example_prompts[0],
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label="Enter your prompt",
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with gr.Column(scale=1):
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generate_btn = gr.Button("Generate", variant="primary")
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example_dropdown.change(lambda ex: ex,
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inputs=[example_dropdown],
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outputs=[input_text])
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# Two status boxes - small (default) and big (during generation)
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small_status_box = gr.Markdown("Ready to generate images",
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performance_plot = gr.Plot(label="Performance Metrics")
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with gr.Accordion("Recent Generations (last 8)", open=False):
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recent_gallery = gr.Gallery(label="Recent Generations",
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columns=3,
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rows=1,
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show_label=True)
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def update_recent_gallery(prompt, results):
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recent_generations.append({
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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"], gen["hidream-dev"], gen["hidream-full"]])
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# Update the Gradio gallery with the new list
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return recent_gallery.update(value=all_images)
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