Update app.py

app.py

@@ -1,16 +1,14 @@
 import gradio as gr
-from gradio_client import Client
+from gradio_client import Client, handle_file
 import random
 import os
-import base64
-import mimetypes
 
 HF_TOKEN = os.environ.get("girlToken")
 
 space_client = Client(
     "prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast",
     token=HF_TOKEN
-)
+    )
 
 LORA_STYLES = [
     'Multiple-Angles', 'Photo-to-Anime', 'Anime-V2', 'Light-Migration',
@@ -23,30 +21,6 @@ LORA_STYLES = [
 MAX_SEED = 2**31 - 1
 
 
-def image_to_gallery_item(local_path):
-    """按照 API 定义，把本地图片转成 Gallery 元素"""
-    mime_type, _ = mimetypes.guess_type(local_path)
-    if not mime_type:
-        mime_type = "image/jpeg"
-
-    with open(local_path, "rb") as f:
-        b64 = base64.b64encode(f.read()).decode("utf-8")
-
-    # url 字段明确支持 base64 encoded image
-    return {
-        "image": {
-            "path": None,
-            "url": f"data:{mime_type};base64,{b64}",
-            "size": os.path.getsize(local_path),
-            "orig_name": os.path.basename(local_path),
-            "mime_type": mime_type,
-            "is_stream": False,
-            "meta": {"_type": "gradio.FileData"}
-        },
-        "caption": None
-    }
-
-
 def infer(
     image,
     prompt,
@@ -57,18 +31,26 @@ def infer(
     steps,
     progress=gr.Progress(track_tqdm=True),
 ):
-    if image is None or not os.path.exists(image):
-        print("未上传图片或路径不存在")
+    if image is None:
+        print("未上传图片")
+        return None, seed
+
+    if not os.path.exists(image):
+        print(f"图片路径不存在: {image}")
         return None, seed
 
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
-    images_input = [image_to_gallery_item(image)]
+    # 关键：用 handle_file 上传到目标 Space，得到远端可访问的文件对象
+    uploaded = handle_file(image)
+
+    # Gallery 元素格式：{"image": <上传后的文件对象>, "caption": None}
+    images_input = [{"image": uploaded, "caption": None}]
 
     print("[调用API] 输入参数：")
-    print(f"  orig_name: {os.path.basename(image)}")
-    print(f"  mime_type: {mimetypes.guess_type(image)[0]}")
+    print(f"  image path: {image}")
+    print(f"  uploaded: {uploaded}")
     print(f"  prompt: {prompt}")
     print(f"  lora_adapter: {lora_adapter}")
     print(f"  seed: {seed}")