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app.py

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+import spaces
+import torch
+from diffusers import BriaPipeline
+from PIL import Image
+import gradio as gr
+
+MODEL_ID = "briaai/BRIA-3.2"
+pipe = BriaPipeline.from_pretrained(MODEL_ID, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+@spaces.GPU(duration=1500)
+def compile_transformer():
+    with spaces.aoti_capture(pipe.transformer) as call:
+        pipe("arbitrary example prompt")
+    
+    exported = torch.export.export(
+        pipe.transformer,
+        args=call.args,
+        kwargs=call.kwargs,
+    )
+    return spaces.aoti_compile(exported)
+
+compiled_transformer = compile_transformer()
+spaces.aoti_apply(compiled_transformer, pipe.transformer)
+
+@spaces.GPU(duration=60)
+def generate_image(prompt, seed=0):
+    torch.manual_seed(seed)
+    image = pipe(prompt).images[0]
+    return image
+
+with gr.Blocks() as demo:
+    gr.Markdown("# BRIA-3.2 Text-to-Image Generator")
+    gr.Markdown("Generate images from text prompts using the BRIA-3.2 model.")
+    
+    with gr.Row():
+        prompt = gr.Textbox(
+            label="Prompt",
+            value="a cat sitting on a chair",
+            interactive=True
+        )
+        seed = gr.Number(
+            label="Seed (0 for random)",
+            value=0,
+            precision=0
+        )
+    
+    generate_btn = gr.Button("Generate Image")
+    output = gr.Image(label="Generated Image", type="pil")
+    
+    generate_btn.click(
+        fn=generate_image,
+        inputs=[prompt, seed],
+        outputs=output
+    )
+    
+    gr.Examples(
+        examples=[
+            ["a futuristic cityscape at sunset"],
+            ["a forest with glowing mushrooms"],
+            ["a steampunk robot drinking tea"],
+            ["an astronaut riding a horse on mars"]
+        ],
+        inputs=[prompt],
+        outputs=output,
+        fn=generate_image,
+        cache_examples="lazy"
+    )
+
+demo.launch()