优化

tests/test_milvus.py

@@ -11,8 +11,8 @@ class TestCreateCollectionFunction(unittest.TestCase):
         fields: List[FieldSchema] = [
             FieldSchema(name="image", dtype=DataType.VARCHAR, max_length=256, is_primary=True, auto_id=False),
             FieldSchema(name="key", dtype=DataType.VARCHAR, max_length=256),
-            # FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=512)  # CLIP ViT-B/32的特征维度为512
-            FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=768)  # CLIP ViT-L/14@336px的特征维度为512
+            FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=512)  # CLIP ViT-B/32的特征维度为512
+            # FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=768)  # CLIP ViT-L/14@336px的特征维度为512
         ]
         MilvusClient().connect().create_collection("pc3", fields, "PC3 图片向量存储")
 
@@ -20,7 +20,7 @@ class TestCreateCollectionFunction(unittest.TestCase):
         index_params = {
             "index_type": "HNSW",
             "metric_type": "IP",  # 内积相似度
-            "params": {"M": 16, "efConstruction": 200}
+            "params": {"M": 32, "efConstruction": 400}
         }
         MilvusClient().connect().create_index("pc3", "vector", index_params)