Update app.py

app.py

@@ -2,42 +2,75 @@ import gradio as gr
 from model_pipelines import load_pipelines, generate_all
 from grace_eval import compute_sample_scores, plot_radar
 import torch
+import time
+from functools import partial
 
-# 强制使用CPU
+# Force CPU and suppress warnings
+torch.set_grad_enabled(False)
 torch.backends.cuda.is_available = lambda: False
 
-pipes = load_pipelines()
+class ModelLoader:
+    _instance = None
+    
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance.models = None
+        return cls._instance
+    
+    def load(self):
+        if self.models is None:
+            print("🔄 Initializing models...")
+            start = time.time()
+            self.models = load_pipelines()
+            print(f"✅ Models loaded in {time.time()-start:.1f}s")
+        return self.models
 
-def compare(prompt):
-    imgs = generate_all(pipes, prompt)
-    return imgs["sd_v1_5"], imgs["openjourney_v4"], imgs["ldm_256"]
+def create_interface():
+    with gr.Blocks(title="🖼️ AI Image Generator Comparison", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("## 🏆 图像生成模型对比实验 (CPU模式)")
+        
+        with gr.Tab("🆚 Arena"):
+            with gr.Row():
+                prompt = gr.Textbox(label="✨ 输入提示词", placeholder="描述您想生成的图像...")
+            with gr.Row():
+                generate_btn = gr.Button("🚀 生成图像", variant="primary")
+            with gr.Row():
+                outputs = [
+                    gr.Image(label="Stable Diffusion v1.5", type="pil"),
+                    gr.Image(label="Openjourney v4", type="pil"),
+                    gr.Image(label="LDM 256", type="pil")
+                ]
+            generate_btn.click(
+                partial(generate_all, ModelLoader().load()),
+                inputs=prompt,
+                outputs=outputs
+            )
 
-def show_leaderboard(prompt):
-    scores = compute_sample_scores(None, prompt)
-    plot_radar(scores)
-    return "radar.png"
+        with gr.Tab("📊 Leaderboard"):
+            with gr.Column():
+                eval_prompt = gr.Textbox(label="评估用提示词")
+                eval_btn = gr.Button("生成雷达图")
+                radar_img = gr.Image(label="GRACE评估结果")
+            eval_btn.click(
+                lambda p: (plot_radar(compute_sample_scores(None, p)) or "radar.png"),
+                inputs=eval_prompt,
+                outputs=radar_img
+            )
 
-with gr.Blocks() as demo:
-    gr.Markdown("# 图像生成模型对比实验 (CPU模式)")
+        with gr.Tab("📝 Report"):
+            try:
+                with open("report.md", "r", encoding="utf-8") as f:
+                    gr.Markdown(f.read())
+            except:
+                gr.Markdown("## 实验报告\n报告加载失败")
 
-    with gr.Tab("Arena"):
-        with gr.Row():
-            prompt = gr.Textbox(label="请输入生成文本", scale=4)
-            btn = gr.Button("生成图像", scale=1)
-        with gr.Row():
-            out1 = gr.Image(label="StableDiffusion v1.5")
-            out2 = gr.Image(label="Openjourney v4")
-            out3 = gr.Image(label="LDM 256")
-        btn.click(compare, inputs=prompt, outputs=[out1, out2, out3])
+    return demo
 
-    with gr.Tab("Leaderboard"):
-        pm = gr.Textbox(label="统一 prompt 用于评价")
-        lb_btn = gr.Button("显示 GRACE 雷达图")
-        lb_img = gr.Image()
-        lb_btn.click(show_leaderboard, inputs=pm, outputs=lb_img)
-
-    with gr.Tab("Report"):
-        markdown = open("report.md", "r", encoding="utf-8").read()
-        gr.Markdown(markdown)
-
-demo.launch()
+if __name__ == "__main__":
+    create_interface().launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True,
+        enable_queue=True
+    )