Update app.py

app.py

@@ -8,7 +8,7 @@ from huggingface_hub import InferenceClient
 from PIL import Image
 
 
-def run_image_to_image(img: Image.Image, prompt: str, model: str) -> Image.Image:
+async def run_image_to_image(img: Image.Image, prompt: str, model: str) -> Image.Image:
     token = os.getenv("HF_TOKEN")
     if not token:
         raise RuntimeError("HF_TOKEN is not set. Please set your Hugging Face token in environment variables.")
@@ -23,7 +23,7 @@ def run_image_to_image(img: Image.Image, prompt: str, model: str) -> Image.Image
             input_bytes = f.read()
 
     try:
-        result = client.image_to_image(
+        result = await client.image_to_image(
             input_bytes,
             prompt=prompt,
             model=model,
@@ -79,8 +79,8 @@ with gr.Blocks(title="图像编辑工具", css=".gradio-container {max-width: 98
     - 将图片背景变成樱花盛开的场景
     """)
 
-    def _run_and_pack(img: Image.Image, p: str, m: str):
-        result_img = run_image_to_image(img, p, m)
+    async def _run_and_pack(img: Image.Image, p: str, m: str):
+        result_img = await run_image_to_image(img, p, m)
         # 保存为临时文件以供下载
         with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
             result_img.save(tmp.name)
@@ -94,98 +94,3 @@ if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0", server_port=7860)
 
 
-import os
-import traceback
-from typing import Optional
-
-import gradio as gr
-from huggingface_hub import InferenceClient
-from PIL import Image
-
-
-def run_image_to_image(img: Image.Image, prompt: str, model: str) -> Image.Image:
-    token = os.getenv("HF_TOKEN")
-    if not token:
-        raise RuntimeError("HF_TOKEN is not set. Please set your Hugging Face token in environment variables.")
-
-    # 直接使用Hugging Face的推理服务
-    client = InferenceClient(token=token)
-
-    # Convert PIL image to bytes
-    with gr.processing_utils.TempFile(suffix=".png") as tmp:
-        img.save(tmp.name, format="PNG")
-        with open(tmp.name, "rb") as f:
-            input_bytes = f.read()
-
-    try:
-        result = client.image_to_image(
-            input_bytes,
-            prompt=prompt,
-            model=model,
-        )
-        return result
-    except Exception as e:
-        traceback.print_exc()
-        error_msg = str(e)
-        if "402" in error_msg:
-            raise RuntimeError("错误402：付费要求。可能是模型需要付费使用或超出免费额度。请检查您的HuggingFace账户状态。")
-        raise
-
-
-with gr.Blocks(title="图像编辑工具", css=".gradio-container {max-width: 980px}") as demo:
-    gr.Markdown("**图像编辑工具** · 上传图片，输入中文或英文提示词，一键完成图像变换")
-
-    with gr.Row():
-        with gr.Column():
-            in_img = gr.Image(type="pil", label="上传图片", height=420)
-            prompt = gr.Textbox(
-                value="将图片中的人物变成卡通风格", 
-                label="提示词（支持中文和英文）", 
-                lines=2,
-                placeholder="请输入您想要的图像变换效果，例如：'将图片变成水彩画风格'、'给图片添加雪景效果'等"
-            )
-            model = gr.Dropdown(
-                choices=[
-                    "svjack/Stable-Diffusion-FineTuned-zh-v2",
-                    "Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers-Distilled",
-                    "tencent/HunyuanImage-3.0"
-                ],
-                value="svjack/Stable-Diffusion-FineTuned-zh-v2",
-                label="模型（均支持中文输入）",
-            )
-            with gr.Row():
-                run_btn = gr.Button("一键转换", variant="primary")
-                clear_btn = gr.Button("清空")
-        with gr.Column():
-            out_img = gr.Image(type="pil", label="输出结果", height=420)
-            download = gr.File(label="下载输出", interactive=False)
-            
-    gr.Markdown("""
-    ### 使用说明
-    1. 上传您想要编辑的图片
-    2. 输入中文或英文提示词，描述您想要的变换效果
-    3. 选择支持中文的模型（所有列出的模型均为免费使用）
-    4. 点击"一键转换"按钮
-    
-    ### 提示词示例
-    - 将图片变成水彩画风格
-    - 给图片添加雪景效果
-    - 将图片中的人物变成卡通风格
-    - 将图片背景变成樱花盛开的场景
-    """)
-
-    def _run_and_pack(img: Image.Image, p: str, m: str):
-        result_img = run_image_to_image(img, p, m)
-        # 保存为临时文件以供下载
-        with gr.processing_utils.TempFile(suffix=".png") as tmp:
-            result_img.save(tmp.name)
-            return result_img, tmp.name
-
-    run_btn.click(fn=_run_and_pack, inputs=[in_img, prompt, model], outputs=[out_img, download])
-    clear_btn.click(lambda: (None, "", None, None), outputs=[in_img, prompt, out_img, download])
-
-
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
-
-