debug：推荐接口

app/api/api_recommendation.py

@@ -178,47 +178,23 @@ async def recommend(
 @router.get("/redis/user_pref")
 async def get_all_user_preferences():
     """
-    获取所有以 user_pref 为前缀的 Redis key 信息，按 account_id 分组
+    获取所有以 user_pref 为前缀的 Redis key 信息
     """
     try:
         from app.service.utils.redis_utils import Redis
         from app.service.recommendation_system.config import REDIS_KEY_USER_PREF_PREFIX
-        import json
         
         # 扫描所有匹配 user_pref:* 的 key
         pattern = f"{REDIS_KEY_USER_PREF_PREFIX}:*"
         keys = Redis.scan_keys(pattern)
         
-        # 按 account_id 分组
+        # 直接返回所有 key 和原始 value
         result = {}
         for key in keys:
-            # 解析 key 格式: user_pref:{account_id}:{category}
-            parts = key.split(':')
-            if len(parts) >= 3:
-                account_id = parts[1]
-                category = parts[2]
-                
-                # 读取对应的值
-                value = Redis.read(key)
-                if value:
-                    try:
-                        vector = json.loads(value)
-                        if account_id not in result:
-                            result[account_id] = {}
-                        result[account_id][category] = {
-                            'key': key,
-                            'preference_vector': vector,
-                            'vector_length': len(vector)
-                        }
-                    except json.JSONDecodeError:
-                        # 如果 JSON 解析失败，保存原始值
-                        if account_id not in result:
-                            result[account_id] = {}
-                        result[account_id][category] = {
-                            'key': key,
-                            'raw_value': value,
-                            'error': 'JSON decode failed'
-                        }
+            # 读取对应的值
+            value = Redis.read(key)
+            if value:
+                result[key] = value
         
         return result
         

app/api/api_route.py

@@ -7,6 +7,7 @@ from app.api import api_design_pre_processing
 from app.api import api_generate_image
 from app.api import api_mannequins_edit
 from app.api import api_pose_transform
+from app.api import api_precompute
 from app.api import api_prompt_generation
 from app.api import api_recommendation
 from app.api import api_test
@@ -21,6 +22,7 @@ router.include_router(api_prompt_generation.router, tags=['prompt_generation'],
 router.include_router(api_design_pre_processing.router, tags=['design_pre_processing'], prefix="/api")
 router.include_router(api_brand_dna.router, tags=['api_brand_dna'], prefix="/api")
 router.include_router(api_recommendation.router, tags=['api_recommendation'], prefix="/api")
+router.include_router(api_precompute.router, tags=['api_precompute'], prefix="/api")
 router.include_router(api_mannequins_edit.router, tags=['api_mannequins_edit'], prefix="/api")
 router.include_router(api_pose_transform.router, tags=['api_pose_transform'], prefix="/api")
 router.include_router(api_clothing_seg.router, tags=['api_clothing_seg'], prefix="/api")

app/service/recommendation_system/precompute.py

@@ -318,8 +318,8 @@ def precompute_system_sketch_vectors(batch_size: int = 1000, retry_times: int =
 def compute_user_preference_vector(
     account_id: int,
     category: str,
-    conn: Optional[pymysql.connections.Connection] = None
-    # max_date: Optional[datetime] = None
+    conn: Optional[pymysql.connections.Connection] = None,
+    max_date: Optional[datetime] = None
 ) -> Optional[np.ndarray]:
     """
     计算用户偏好向量
@@ -519,16 +519,16 @@ def run_precompute():
     logger.info("=" * 50)
     
     # 1. 优化数据库表结构
-    logger.info("\n[1/5] 优化数据库表结构...")
-    optimize_database_table()
+    # logger.info("\n[1/5] 优化数据库表结构...")
+    # optimize_database_table()
     
     # # 2. 创建 Milvus 集合
     # logger.info("\n[2/5] 创建 Milvus 集合...")
     # create_collection()
     
     # 3. 历史数据迁移
-    logger.info("\n[3/5] 历史数据迁移...")
-    migrate_historical_data()
+    # logger.info("\n[3/5] 历史数据迁移...")
+    # migrate_historical_data()
     
     # # 4. 系统图向量预计算
     # logger.info("\n[4/5] 系统图向量预计算...")
@@ -544,13 +544,13 @@ def run_precompute():
 
 
 if __name__ == "__main__":
-    # 1. 优化数据库表结构
-    logger.info("\n[1/5] 优化数据库表结构...")
-    optimize_database_table()
-
-    # 3. 历史数据迁移
-    logger.info("\n[3/5] 历史数据迁移...")
-    migrate_historical_data()
+    # # 1. 优化数据库表结构
+    # logger.info("\n[1/5] 优化数据库表结构...")
+    # optimize_database_table()
+    #
+    # # 3. 历史数据迁移
+    # logger.info("\n[3/5] 历史数据迁移...")
+    # migrate_historical_data()
 
     # 5. 初始用户偏好向量生成
     logger.info("\n[5/5] 初始用户偏好向量生成...")