新推荐接口first commit

app/service/recommendation_system/config.py

@@ -2,12 +2,7 @@
 推荐系统配置
 """
 import os
-from app.core.config import (
-    DB_CONFIG, DB_HOST, DB_PORT, DB_USERNAME, DB_PASSWORD, DB_NAME,
-    REDIS_HOST, REDIS_PORT, REDIS_DB,
-    MILVUS_URL, MILVUS_TOKEN, MILVUS_ALIAS,
-    MINIO_URL, MINIO_ACCESS, MINIO_SECRET, MINIO_SECURE
-)
+from app.core.config import settings
 
 # Milvus 集合名称
 MILVUS_COLLECTION_SKETCH_VECTORS = "sketch_vectors_norm"
@@ -63,11 +58,10 @@ TABLE_SYS_FILE = "t_sys_file"
 
 # MySQL 连接配置（用于推荐系统）
 MYSQL_CONFIG = {
-    "host": DB_HOST,
-    "port": DB_PORT,
-    "user": DB_USERNAME,
-    "password": DB_PASSWORD,
-    "database": DB_NAME,
+    "host": settings.MYSQL_HOST,
+    "port": settings.MYSQL_PORT,
+    "user": settings.MYSQL_USER,
+    "password": settings.MYSQL_PASSWORD,
+    "database": settings.MYSQL_DB,
     "charset": "utf8mb4"
 }
-

app/service/recommendation_system/milvus_client.py

@@ -6,7 +6,7 @@ from typing import List, Dict, Optional, Any
 import numpy as np
 from pymilvus import MilvusClient, FieldSchema, CollectionSchema, DataType, connections, Collection
 
-from app.core.config import MILVUS_URL, MILVUS_TOKEN, MILVUS_ALIAS
+from app.core.config import settings
 from app.service.recommendation_system.config import MILVUS_COLLECTION_SKETCH_VECTORS, RECOMMENDATION_CONFIG
 
 logger = logging.getLogger(__name__)
@@ -21,9 +21,9 @@ def get_milvus_client() -> MilvusClient:
     if _milvus_client is None:
         try:
             _milvus_client = MilvusClient(
-                uri=MILVUS_URL,
-                token=MILVUS_TOKEN,
-                db_name=MILVUS_ALIAS
+                uri=settings.MILVUS_URL,
+                token=settings.MILVUS_TOKEN,
+                db_name=settings.MILVUS_DB,
             )
             logger.info("Milvus 客户端连接成功")
         except Exception as e:
@@ -56,7 +56,7 @@ def create_collection():
     try:
         # 解析 Milvus URL
         # 处理 http://host.docker.internal:19530 格式
-        url_clean = MILVUS_URL.replace("http://", "").replace("https://", "")
+        url_clean = settings.MILVUS_URL.replace("http://", "").replace("https://", "")
         if ":" in url_clean:
             host, port_str = url_clean.split(":", 1)
             port = int(port_str)
@@ -68,10 +68,10 @@ def create_collection():
         # 连接到 Milvus（如果未连接）
         try:
             connections.connect(
-                alias=MILVUS_ALIAS,
+                alias=settings.MILVUS_ALIAS,
                 host=host,
                 port=port,
-                token=MILVUS_TOKEN if MILVUS_TOKEN else None
+                token=settings.MILVUS_TOKEN if settings.MILVUS_TOKEN else None
             )
             logger.info(f"已连接到 Milvus: {host}:{port}")
         except Exception as conn_e:
@@ -106,7 +106,7 @@ def create_collection():
         collection = Collection(
             name=MILVUS_COLLECTION_SKETCH_VECTORS,
             schema=schema,
-            using=MILVUS_ALIAS
+            using=settings.MILVUS_ALIAS
         )
 
         # 创建索引
@@ -200,10 +200,10 @@ def query_vectors_by_paths(paths: List[str]) -> Dict[str, Dict]:
 
 
 def search_similar_vectors(
-    query_vector: np.ndarray,
-    category: str,
-    topk: int = 500,
-    style: Optional[str] = None
+        query_vector: np.ndarray,
+        category: str,
+        topk: int = 500,
+        style: Optional[str] = None
 ) -> List[Dict]:
     """
     向量相似度检索
@@ -292,4 +292,3 @@ def query_random_candidates(category: str, style: Optional[str] = None, limit: i
     except Exception as e:
         logger.error(f"随机查询候选失败: {e}", exc_info=True)
         return []
-