Qdrant 1.16: 계층형 멀티테넌시와 효율적인 벡터 검색 실전 가이드

client.create_collection(
    collection_name="shared_collection",
    vectors_config=models.VectorParams(size=768, distance=models.Distance.COSINE),
    hnsw_config=models.HnswConfigDiff(
        payload_m=16, # Build graph per tenant
        m=0,          # Disable global graph
    ),
)

client.upsert(
    collection_name=collection_name,
    points=points,
    shard_key_selector=models.ShardKeyWithFallback(
        target="user_3",
        fallback="default"
    )
)