fix

api_routes.py

@@ -983,7 +983,7 @@ async def upload_file(
         # 如果没有扩展名，使用空扩展名（保持用户上传文件的原始格式）
 
         # 生成唯一ID
-        unique_id = str(uuid.uuid4()).replace('-', '')
+        unique_id = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
         extra_meta_base = {
             "source": "upload_file",
             "file_type": fileType,
@@ -1122,7 +1122,7 @@ async def analyze_face(
     contents = await file.read()
     np_arr = np.frombuffer(contents, np.uint8)
     image = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
-    original_md5_hash = str(uuid.uuid4()).replace('-', '')
+    original_md5_hash = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
     original_image_filename = f"{original_md5_hash}_original.webp"
     original_image_path = os.path.join(IMAGES_DIR, original_image_filename)
     save_image_high_quality(image, original_image_path, quality=SAVE_QUALITY, upload_to_bos=False)
@@ -1307,7 +1307,7 @@ async def analyze_face(
                     continue
 
                 # 生成MD5哈希
-                original_md5_hash = str(uuid.uuid4()).replace("-", "")
+                original_md5_hash = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
                 original_image_filename = f"{original_md5_hash}_original.webp"
 
                 logger.info(
@@ -1564,7 +1564,7 @@ async def search_by_image(
         image_data = await file.read()
 
         # 保存临时图片文件
-        temp_image_path = f"/tmp/search_image_{uuid.uuid4().hex}.webp"
+        temp_image_path = f"/tmp/search_image_ugc_{uuid.uuid4().hex}.webp"
         try:
             # 解码图片
             np_arr = np.frombuffer(image_data, np.uint8)
@@ -2180,7 +2180,7 @@ async def restore_old_photo(
 
     try:
         contents = await file.read()
-        original_md5_hash = str(uuid.uuid4()).replace('-', '')
+        original_md5_hash = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
         # 如果前端传递了md5参数则使用，否则使用original_md5_hash
         actual_md5 = md5 if md5 else original_md5_hash
         restored_filename = f"{actual_md5}_restore.webp"
@@ -2326,7 +2326,7 @@ async def colorize_photo(
 
     try:
         contents = await file.read()
-        original_md5_hash = str(uuid.uuid4()).replace('-', '')
+        original_md5_hash = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
         # 如果前端传递了md5参数则使用，否则使用original_md5_hash
         actual_md5 = md5 if md5 else original_md5_hash
         colored_filename = f"{actual_md5}_upcolor.webp"
@@ -2558,7 +2558,7 @@ async def anime_stylize_photo(
                 f"Original image already exists for anime style: {original_filename}")
             original_bos_uploaded = False
 
-        styled_uuid = uuid.uuid4().hex
+        styled_uuid = f"ugc_{uuid.uuid4().hex}"
         styled_filename = f"{styled_uuid}_anime_style_{style_type}.webp"
 
         # 获取风格描述
@@ -2657,7 +2657,7 @@ async def grayscale_photo(
 
     try:
         contents = await file.read()
-        original_md5_hash = str(uuid.uuid4()).replace('-', '')
+        original_md5_hash = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
         grayscale_filename = f"{original_md5_hash}_grayscale.webp"
 
         logger.info(f"Starting image grayscale: {file.filename}, size={file.size}, md5={original_md5_hash}")
@@ -2772,7 +2772,7 @@ async def upscale_photo(
 
     try:
         contents = await file.read()
-        original_md5_hash = str(uuid.uuid4()).replace('-', '')
+        original_md5_hash = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
         # 如果前端传递了md5参数则使用，否则使用original_md5_hash
         actual_md5 = md5 if md5 else original_md5_hash
         upscaled_filename = f"{actual_md5}_upscale.webp"
@@ -2936,7 +2936,7 @@ async def remove_background(
             logger.info(f"User selected robustVideoMatting model but no face detected in image, switching to {model} model")
 
         # 生成唯一ID
-        unique_id = str(uuid.uuid4()).replace('-', '')  # 32位UUID
+        unique_id = f"ugc_{str(uuid.uuid4()).replace('-', '')}"  # 32位UUID加上ugc_前缀
 
         # 根据是否有透明背景决定文件扩展名
         if background_color and background_color.lower() != "none":
@@ -3111,7 +3111,7 @@ async def rvm_remove_background(
 
     try:
         contents = await file.read()
-        unique_id = str(uuid.uuid4()).replace('-', '')  # 32位UUID
+        unique_id = f"ugc_{str(uuid.uuid4()).replace('-', '')}"  # 32位UUID加上ugc_前缀
 
         # 根据是否有透明背景决定文件扩展名
         if background_color and background_color.lower() != "none":
@@ -3361,7 +3361,7 @@ async def split_grid_image(
 
     try:
         contents = await file.read()
-        original_md5_hash = str(uuid.uuid4()).replace('-', '')
+        original_md5_hash = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
 
         # 根据宫格类型确定行列数
         if grid_type == 4:
@@ -3519,7 +3519,7 @@ async def compress_image(
 
     try:
         contents = await file.read()
-        unique_id = str(uuid.uuid4()).replace('-', '')[:32]  # 12位随机ID
+        unique_id = f"ugc_{str(uuid.uuid4()).replace('-', '')}"  # 带有 ugc_ 前缀的 UUID
         compressed_filename = f"{unique_id}_compress.{outputFormat.lower()}"
         logger.info(
             f"Starting to compress image: {file.filename}, "
@@ -4152,7 +4152,7 @@ async def match_celebrity_face(
                 raise HTTPException(status_code=400,
                                     detail="图片中未检测到人脸，请重新上传。")
 
-        temp_filename = f"{uuid.uuid4().hex}_celebrity_query.webp"
+        temp_filename = f"ugc_{uuid.uuid4().hex}_celebrity_query.webp"
         temp_path = os.path.join(IMAGES_DIR, temp_filename)
         if not save_image_high_quality(image, temp_path, quality=SAVE_QUALITY):
             raise HTTPException(status_code=500,
@@ -4307,7 +4307,7 @@ async def match_celebrity_face(
 
         face_filename = None
         if crop is not None and crop.size > 0:
-            face_filename = f"{uuid.uuid4().hex}_face_1.webp"
+            face_filename = f"ugc_{uuid.uuid4().hex}_face_1.webp"
             face_path = os.path.join(IMAGES_DIR, face_filename)
             if not save_image_high_quality(crop, face_path,
                                            quality=SAVE_QUALITY):
@@ -4414,8 +4414,8 @@ async def face_similarity_verification(
         contents2 = await file2.read()
 
         # 生成唯一标识符
-        md5_hash1 = str(uuid.uuid4()).replace('-', '')
-        md5_hash2 = str(uuid.uuid4()).replace('-', '')
+        md5_hash1 = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
+        md5_hash2 = f"ugc_{str(uuid.uuid4()).replace('-', '')}"
 
         # 生成文件名
         original_filename1 = f"{md5_hash1}_original1.webp"