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app.py

@@ -8,6 +8,17 @@ from pathlib import Path
 
 import gradio as gr
 
+try:
+    import spaces
+except Exception:  # local dev outside HF Spaces
+    class _SpacesShim:
+        @staticmethod
+        def GPU(*args, **kwargs):
+            def deco(fn):
+                return fn
+            return deco
+    spaces = _SpacesShim()
+
 ROOT = Path(__file__).resolve().parent
 sys.path.insert(0, str(ROOT))
 
@@ -79,6 +90,7 @@ def render_lineage(provenance: dict) -> str:
     """
 
 
+@spaces.GPU(duration=180)
 def generate(lora_a: str, lora_b: str, blend_a: int, prompt: str, seed: int, size: int):
     if not prompt.strip():
         raise gr.Error("Give the image a prompt first.")
@@ -119,7 +131,7 @@ def build_demo():
                 blend = gr.Slider(0, 100, value=100, step=1, label="Blend: A % / B %")
                 prompt = gr.Textbox(label="Describe the imagined instrument image", value="a musician holding a newly invented bowl-shaped string instrument in a small warm room", lines=3)
                 seed = gr.Number(label="Seed", value=42, precision=0)
-                size = gr.Dropdown(label="Image size", choices=[512, 768, 1024], value=768)
+                size = gr.Slider(512, 1024, value=768, step=256, label="Image size")
                 btn = gr.Button("Generate with live LoRA", variant="primary")
             with gr.Column(scale=2):
                 output_image = gr.Image(label="Generated image", type="pil")

requirements.txt

@@ -1,4 +1,4 @@
-gradio>=5.0
+gradio==5.49.1
 pydantic>=2.0
 PyYAML>=6.0
 Pillow>=10.0
@@ -6,6 +6,7 @@ requests>=2.31
 huggingface_hub>=0.26,<1.0
 peft>=0.14
 accelerate>=1.0
+spaces
 torch
 diffusers @ git+https://github.com/huggingface/diffusers.git
 transformers