Update app.py

app.py

@@ -1,9 +1,7 @@
 import gradio as gr
-from gradio_client import Client
+from gradio_client import Client, handle_file
 import random
 import os
-import base64
-import mimetypes
 
 space_client = Client("prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast")
 
@@ -18,37 +16,6 @@ LORA_STYLES = [
 MAX_SEED = 2**31 - 1
 
 
-def encode_image_for_gallery(image_path):
-    """将图片转为 base64 data URL，嵌入 url 字段传给远端"""
-    if not image_path or not isinstance(image_path, str):
-        return None
-    if not os.path.exists(image_path):
-        print(f"文件不存在: {image_path}")
-        return None
-
-    mime_type, _ = mimetypes.guess_type(image_path)
-    if not mime_type:
-        mime_type = "image/png"
-
-    with open(image_path, "rb") as f:
-        b64 = base64.b64encode(f.read()).decode("utf-8")
-
-    data_url = f"data:{mime_type};base64,{b64}"
-
-    return {
-        "image": {
-            "path": None,
-            "url": data_url,          # base64 嵌入这里
-            "size": os.path.getsize(image_path),
-            "orig_name": os.path.basename(image_path),
-            "mime_type": mime_type,
-            "is_stream": False,
-            "meta": {}
-        },
-        "caption": None
-    }
-
-
 def infer(
     image,
     prompt,
@@ -59,28 +26,26 @@ def infer(
     steps,
     progress=gr.Progress(track_tqdm=True),
 ):
-    images_input = []
-
-    if image is not None:
-        if isinstance(image, list):
-            for im in image:
-                obj = encode_image_for_gallery(im)
-                if obj:
-                    images_input.append(obj)
-        else:
-            obj = encode_image_for_gallery(image)
-            if obj:
-                images_input.append(obj)
+    if image is None:
+        print("未上传图片")
+        return None, seed
 
-    if len(images_input) == 0:
-        print("未检测到有效图片，请上传图片后再试。")
+    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)
 
+    # 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"  images count: {len(images_input)}")
+    print(f"  image path: {image}")
+    print(f"  uploaded: {uploaded}")
     print(f"  prompt: {prompt}")
     print(f"  lora_adapter: {lora_adapter}")
     print(f"  seed: {seed}")
@@ -105,14 +70,15 @@ def infer(
 
         if isinstance(image_info, dict):
             img_out = image_info.get("path") or image_info.get("url")
-            return img_out, int(seed_used)
         else:
-            return image_info, int(seed_used)
+            img_out = image_info
+
+        return img_out, int(seed_used)
 
     except Exception as e:
         import traceback
         traceback.print_exc()
-        print(f"[调用API] 调用接口异常: {e}")
+        print(f"[调用API] 异常: {e}")
         return None, seed