fix code

backend/app/ai/service/image_service.py

@@ -355,6 +355,13 @@ class ImageService:
                     
                     await db.commit()
                     task_processing_success = True
+                    # step 6 create scene task
+                    try:
+                        from backend.app.ai.service.sentence_service import SentenceService
+                        if task:
+                            await SentenceService.create_scene_task(task.image_id, task.user_id, 'scene_sentence')
+                    except Exception as scene_err:
+                        logger.error(f"Failed to create scene sentence task for task {task_id}: {str(scene_err)}")
                     
                 except Exception as e:
                     await db.rollback()

backend/app/ai/service/rate_limit_service.py

@@ -75,8 +75,8 @@ class RateLimitService:
         # if limit is not None:
         #     return int(limit)
         
-        # 默认限制为2个任务
-        return 2
+        # 默认限制为3个任务
+        return 3
     
     @staticmethod
     async def set_user_task_limit(user_id: int, limit: int, expire_seconds: int = 3600) -> None:

backend/app/ai/service/recording_service.py

@@ -25,6 +25,7 @@ from backend.app.ai.crud.recording_crud import recording_dao
 
 # Import the image_text_service for fetching image text records
 from backend.app.ai.service.image_text_service import image_text_service
+from backend.common.exception import errors
 
 logger = logging.getLogger(__name__)
 
@@ -372,7 +373,7 @@ class RecordingService:
 
         # 检查用户积分是否足够（现在积分没有过期概念）
         if not await points_service.check_sufficient_points(user_id, SPEECH_ASSESSMENT_COST):
-            raise RuntimeError('积分不足，请获取积分后继续使用')
+            raise errors.ForbiddenError(msg='积分不足，请获取积分后继续使用')
 
         try:
             # 调用腾讯云SOE API进行语音评估

backend/app/ai/service/sentence_service.py

@@ -159,7 +159,7 @@ class SentenceService:
         except Exception:
             parsed = {}
 
-        print(parsed)
+        # print(parsed)
         items = []
         sc = parsed.get("sentence") or {}
         for idx, d in enumerate(sc.get("list", []), start=1):