Update app.py

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from gradio_client import Client
 import random
 import os
+import base64
 
 # API client for the external Space
 space_client = Client("prithivMLmods/Qwen-Image-Edit-2511-LoRAs-Fast")
@@ -29,15 +30,17 @@ LORA_STYLES = [
 ]
 MAX_SEED = 2**32-1
 
-def safe_image_path(path):
-    """Ensure the given path points to an existing, readable file."""
-    if not path or not isinstance(path, str):
+def encode_image_to_base64(image_path):
+    """Read image file and encode as base64 string."""
+    if not image_path or not isinstance(image_path, str):
+        return None
+    try:
+        with open(image_path, "rb") as f:
+            encoded = base64.b64encode(f.read()).decode("utf-8")
+        return encoded
+    except Exception as e:
+        print(f"无法读取图片或编码失败: {image_path}: {e}")
         return None
-    if os.path.isfile(path):
-        return path
-    # Try to handle Gradio's nested path structure if needed
-    # (Could be adjusted depending how Gradio saves upload images)
-    return None
 
 def infer(
     image,
@@ -49,32 +52,32 @@ def infer(
     steps,
     progress=gr.Progress(track_tqdm=True),
 ):
-    # Prepare images input as per API (expects Gallery [list of dicts])
-    images = []
+    # Process input image(s) as base64 for API (instead of file path)
+    images_input = []
     if image is not None:
         if isinstance(image, list):  # Gradio Gallery
             for im in image:
-                file_path = safe_image_path(im)
-                if file_path:
-                    images.append({"image": {"path": file_path}, "caption": None})
+                img_b64 = encode_image_to_base64(im)
+                if img_b64:
+                    images_input.append({"image": img_b64, "caption": None})
                 else:
-                    print(f"警告: 路径无效或找不到文件: {im}")
+                    print(f"警告: 路径无效或无法读取: {im}")
         else:
-            file_path = safe_image_path(image)
-            if file_path:
-                images.append({"image": {"path": file_path}, "caption": None})
+            img_b64 = encode_image_to_base64(image)
+            if img_b64:
+                images_input.append({"image": img_b64, "caption": None})
             else:
-                print(f"警告: 路径无效或找不到文件: {image}")
+                print(f"警告: 路径无效或无法读取: {image}")
 
-    if len(images) == 0:
-        print("未检测到有效图片路径，未能上传图片。")
+    if len(images_input) == 0:
+        print("未检测到有效图片，未能上传图片。")
         return None, seed
 
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
     print("[调用API] space_client.predict 输入参数：")
-    print(f"  images: {images}")
+    print(f"  images (base64): {[len(i['image']) for i in images_input]}")
     print(f"  prompt: {prompt}")
     print(f"  lora_adapter: {lora_adapter}")
     print(f"  seed: {seed}")
@@ -83,8 +86,10 @@ def infer(
     print(f"  steps: {steps}")
 
     try:
+        # The API might expect images as list of base64 dicts instead of {path: ...}
+        # If error persists, check the API interface definition.
         result = space_client.predict(
-            images=images,
+            images=images_input,
             prompt=prompt,
             lora_adapter=lora_adapter,
             seed=float(seed),
@@ -94,16 +99,13 @@ def infer(
             api_name="/infer",
         )
         print(f"[调用API] space_client.predict 返回值: {result}")
-        # result is a tuple: (image_dict, seed)
         image_info, seed_used = result
-        # The API may return image at .url or .path, we use .url if available
-        img_url = image_info.get("url") or image_info.get("path")
+        img_url = image_info.get("url") or image_info.get("path") or None
         return img_url, seed_used
     except Exception as e:
         import traceback
         traceback.print_exc()
         print(f"[调用API] 调用接口异常: {e}")
-        # More verbose error message for image-processing errors
         if hasattr(e, 'message') and "Could not process uploaded images" in str(e):
             print(
                 "\n[错误] 上传图片处理失败。请确保图片文件有效且未损坏。\n"