add requirement file

app.py

@@ -3,25 +3,40 @@ import gradio as gr
 from diffusers import StableDiffusionPipeline
 import torch
 
-# 初始化模型（免费版Space选择小模型）
+# 在Space环境中检测设备
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"使用设备: {device}")
+
+# 初始化模型（适配Space环境）
 model = StableDiffusionPipeline.from_pretrained(
     "CompVis/stable-diffusion-v1-4",
-    torch_dtype=torch.float16,
+    torch_dtype=torch.float16 if device == "cuda" else torch.float32,
     use_safetensors=True,
-    low_cpu_mem_usage=True  # 节省内存
-).to("cuda") if torch.cuda.is_available() else None  # 兼容CPU模式
+    safety_checker=None,  # 根据需要可开启或关闭
+    variant="fp16" if device == "cuda" else None,
+    low_cpu_mem_usage=True
+)
+model = model.to(device)
 
 def generate(prompt):
-    if model is None:
-        return "当前环境不支持图像生成"
-    image = model(prompt, num_inference_steps=15).images[0]
-    return image
+    if not prompt:
+        return None, "请输入有效的提示词"
+    try:
+        image = model(prompt, num_inference_steps=15).images[0]
+        return image, "生成成功!"
+    except Exception as e:
+        return None, f"生成失败: {str(e)}"
 
 # 基础界面
 interface = gr.Interface(
     fn=generate,
     inputs=gr.Textbox(label="输入表情包描述"),
-    outputs=gr.Image(label="生成结果"),
+    outputs=[
+        gr.Image(label="生成结果"),
+        gr.Textbox(label="状态")
+    ],
     examples=[["一只生气的猫"], ["跳舞的香蕉"]]
 )
-interface.launch()
+
+# Hugging Face Space推荐的启动方式
+interface.launch(share=False, server_name="0.0.0.0")

requirement.txt

@@ -0,0 +1,6 @@
+diffusers>=0.23.1
+transformers>=4.30.0
+accelerate>=0.20.0
+torch>=2.0.0
+gradio>=3.32.0
+safetensors