# app.py
import gradio as gr
from diffusers import StableDiffusionPipeline
import torch
from PIL import Image, ImageFilter

# 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(
    "stabilityai/sd-turbo",
    torch_dtype=torch.float16 if device == "cuda" else torch.float32,
    use_safetensors=True,
    safety_checker=None,
    variant="fp16" if device == "cuda" else None,
    low_cpu_mem_usage=True
).to(device)

# 性能优化
if device == "cuda":
    model.enable_xformers_memory_efficient_attention()
    model.enable_model_cpu_offload()

def validate_input(prompt):
    """输入验证"""
    if not prompt:
        raise ValueError("请输入有效描述")
    if len(prompt) > 100:
        raise ValueError("提示词过长（最多100字符）")
    if not any('\u4e00' <= c <= '\u9fff' for c in prompt):
        raise ValueError("请至少包含一个中文字符")
    return prompt.strip()

def post_process(image):
    """图像后处理"""
    return image.filter(ImageFilter.SHARPEN).filter(ImageFilter.UnsharpMask(radius=2, percent=150))

def generate(prompt):
    try:
        valid_prompt = validate_input(prompt)
        steps = 4 if device == "cuda" else 15
        image = model(
            valid_prompt,
            num_inference_steps=steps,
            guidance_scale=2.0,
            height=768 if device == "cuda" else 512,
            width=768 if device == "cuda" else 512
        ).images[0]
        return post_process(image), "🎉 生成成功！点击图片可下载"
    except Exception as e:
        return None, f"❌ 错误：{str(e)}"
    
# 界面构建
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("## 🎭 AI表情包工坊")
    
    with gr.Row():
        input_box = gr.Textbox(label="输入描述", placeholder="例如：打工人的周一早晨...")
        generate_btn = gr.Button("生成", variant="primary")
    
    with gr.Row():
        image_out = gr.Image(label="生成结果", show_label=False, type="pil")
        status_box = gr.Textbox(label="状态", interactive=False)
    
    gr.Examples(
        examples=[["熊猫头说'我太难了'"], ["流泪猫猫头配文'真的栓Q'"]],
        inputs=input_box
    )

    generate_btn.click(
        generate,
        inputs=input_box,
        outputs=[image_out, status_box]
    )

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0")