Create app.py

app.py

@@ -0,0 +1,73 @@
+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline
+
+# 全域變數
+pipe = None
+
+def load_model_fn(model_id, device_choice):
+    global pipe
+    try:
+        # 強制邏輯：如果是 CPU，一定要用 float32 才能跑
+        if device_choice == "cpu":
+            dtype = torch.float32
+        else:
+            dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+        
+        yield f"⏳ 正在載入模型至 {device_choice.upper()}... (這可能需要幾分鐘)"
+        
+        pipe = StableDiffusionPipeline.from_pretrained(
+            model_id, 
+            torch_dtype=dtype,
+            use_safetensors=True
+        )
+        pipe.to(device_choice)
+        
+        yield f"✅ 成功載入：{model_id} ({device_choice.upper()})"
+    except Exception as e:
+        yield f"❌ 載_入失敗：{str(e)}"
+
+def generate_fn(prompt, steps, guidance):
+    global pipe
+    if pipe is None:
+        return None, "⚠️ 請先點擊『載入模型』！"
+    
+    try:
+        image = pipe(
+            prompt, 
+            num_inference_steps=int(steps), 
+            guidance_scale=guidance
+        ).images[0] # 確保回傳單張圖片
+        return image, "✨ 生成成功！"
+    except Exception as e:
+        return None, f"❌ 錯誤：{str(e)}"
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🛠️ CPU 優化版 Stable Diffusion 控制台")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("### 1. 模型設定")
+            model_input = gr.Textbox(
+                label="Hugging Face Model ID", 
+                value="runwayml/stable-diffusion-v1-5"
+            )
+            # 這裡預設改為 "cpu"
+            device_radio = gr.Radio(["cpu", "cuda"], value="cpu", label="執行設備 (預設 CPU)")
+            load_btn = gr.Button("🔄 載入模型", variant="secondary")
+            load_status = gr.Markdown("系統狀態：等待指令")
+            
+            gr.Markdown("### 2. 繪圖參數")
+            prompt = gr.Textbox(label="提示詞 (Prompt)", lines=3, placeholder="An astronaut riding a horse")
+            steps = gr.Slider(1, 50, value=20, step=1, label="步數 (CPU 建議 15-20)")
+            guidance = gr.Slider(1, 20, value=7.5, step=0.5, label="提示詞強度")
+            gen_btn = gr.Button("🚀 開始生成", variant="primary")
+
+        with gr.Column(scale=2):
+            output_img = gr.Image(label="生成結果")
+            status_msg = gr.Textbox(label="執行訊息", interactive=False)
+
+    load_btn.click(fn=load_model_fn, inputs=[model_input, device_radio], outputs=load_status)
+    gen_btn.click(fn=generate_fn, inputs=[prompt, steps, guidance], outputs=[output_img, status_msg])
+
+demo.launch()