Update app.py

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from gradio_client import Client, handle_file
 import random
 import os
+from PIL import Image
 
 # API client for the external Space
 space_client = Client("prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast")
@@ -30,11 +31,20 @@ LORA_STYLES = [
 MAX_SEED = 2**31 - 1
 
 def encode_image_to_gallery_dict(image_path):
-    if not image_path or not isinstance(image_path, str):
+    """
+    Returns the dict structure required for GalleryData, containing "image" (binary data) and "orig_name".
+    This directly loads the image and provides the binary data instead of a path, fixing the GalleryData validation error.
+    """
+    if not image_path or not isinstance(image_path, str) or not os.path.isfile(image_path):
         return None
     try:
-        # Gallery with type="filepath" expects a dictionary with file path
-        return {"path": image_path, "orig_name": os.path.basename(image_path), "meta": {"_type": "gradio.FileData"}}
+        # Read image into bytes
+        with open(image_path, "rb") as f:
+            image_bytes = f.read()
+        return {
+            "image": image_bytes,
+            "orig_name": os.path.basename(image_path)
+        }
     except Exception as e:
         print(f"无法读取图片: {image_path}: {e}")
         return None
@@ -49,7 +59,7 @@ def infer(
     steps,
     progress=gr.Progress(track_tqdm=True),
 ):
-    # Prepare images_input as a list of dicts of file data (not as tuples)
+    # Prepare images_input as a list of dicts containing "image" (binary data)
     images_input = []
     if image is not None:
         if isinstance(image, list):
@@ -84,7 +94,7 @@ def infer(
     print(f"  steps: {steps}")
 
     try:
-        # Use plain list of dicts as images parameter
+        # Use plain list of dicts with "image" key as images parameter
         result = space_client.predict(
             images=images_input,
             prompt=prompt,