Update app.py

app.py

@@ -1,61 +1,46 @@
 import gradio as gr
-import torch
-from optimum.intel import OVZImagePipeline
-
-# ===== Load model (only once) =====
-pipe = OVZImagePipeline.from_pretrained(
-    "hsuwill000/Z-Image-Turbo-ov",
-    device="cpu"
-)
-
-# ===== Inference function =====
-def generate_image(prompt, height, width, steps, seed):
-    if seed == -1:
-        generator = torch.Generator("cpu")
-    else:
-        generator = torch.Generator("cpu").manual_seed(int(seed))
-
-    image = pipe(
-        prompt=prompt,
-        height=int(height),
-        width=int(width),
-        num_inference_steps=int(steps),
-        guidance_scale=0.0,  # Turbo 必須 0
-        generator=generator,
-    ).images[0]
+from inference import generate
 
-    return image
+default_prompt = """Cinematic portrait of a Japanese girl as Shinobu Kocho, realistic facial features, gradient purple compound eyes, intricate butterfly hair ornament, wearing silk haori with butterfly wing patterns, soft moonlight, hyper-realistic, depth of field, purple butterfly particles, ethereal lighting"""
 
 
-# ===== Default prompt =====
-default_prompt = """Cinematic portrait of a Japanese girl as Shinobu Kocho, realistic facial features, gradient purple compound eyes, intricate butterfly hair ornament, wearing silk haori with butterfly wing patterns, soft moonlight, hyper-realistic, depth of field, purple butterfly particles, 8k resolution, ethereal lighting"""
+def ui_generate(prompt, height, width, steps, seed):
+    return generate(
+        prompt=prompt,
+        height=int(height),
+        width=int(width),
+        steps=int(steps),
+        seed=int(seed),
+    )
 
 
-# ===== Gradio UI =====
 with gr.Blocks() as demo:
-    gr.Markdown("# 🚀 Z-Image Turbo (OpenVINO CPU)")
+    gr.Markdown("## 🚀 Z-Image Turbo (Fast Mode)")
 
     with gr.Row():
         with gr.Column():
-            prompt = gr.Textbox(label="Prompt", value=default_prompt, lines=5)
+            prompt = gr.Textbox(value=default_prompt, lines=4, label="Prompt")
 
-            height = gr.Slider(256, 1024, value=512, step=64, label="Height")
-            width = gr.Slider(256, 1024, value=512, step=64, label="Width")
+            height = gr.Slider(256, 1024, value=512, step=64)
+            width = gr.Slider(256, 1024, value=512, step=64)
 
-            steps = gr.Slider(1, 20, value=9, step=1, label="Inference Steps")
-            seed = gr.Number(value=-1, label="Seed (-1 = random)")
+            steps = gr.Slider(1, 20, value=9, step=1)
+            seed = gr.Number(value=-1)
 
-            run_btn = gr.Button("Generate")
+            btn = gr.Button("Generate")
 
         with gr.Column():
-            output = gr.Image(label="Generated Image")
+            out = gr.Image()
 
-    run_btn.click(
-        fn=generate_image,
+    btn.click(
+        fn=ui_generate,
         inputs=[prompt, height, width, steps, seed],
-        outputs=output,
+        outputs=out,
     )
 
-# ===== Launch =====
+
+
+demo.queue()
+
 if __name__ == "__main__":
     demo.launch()