Don’t Accept Slow Search

# Hybrid search with business-logic reranking
results = client.query_points(
    collection_name="products",
    prefetch=[
        Prefetch(query=dense_emb, using="dense", limit=100),
        Prefetch(query=sparse_emb, using="sparse", limit=100),
    ],
    query=FusionQuery(fusion=Fusion.RRF),
    query_filter=Filter(must=[
        FieldCondition("in_stock", match=MatchValue(True)),
        FieldCondition("category", match=MatchValue("shoes")),
        FieldCondition("price", range=Range(lte=150.0)),
    ]),
    limit=20,
)

# Payload-based multi-tenancy
client.create_collection(
    "marketplace",
    vectors_config=VectorParams(size=1536, distance="Cosine"),
    hnsw_config=HnswConfigDiff(payload_m=16, m=0),
    on_disk_payload=True,
)

# Create per-tenant index
client.create_payload_index(
    "marketplace", "tenant_id",
    field_schema=PayloadSchemaType.KEYWORD,
    is_tenant=True,  # enables per-tenant HNSW
)

# Query scoped to tenant
client.query_points(
    "marketplace",
    query=embedding,
    query_filter=Filter(must=[
        FieldCondition("tenant_id", match=MatchValue("brand_123"))
    ]),
    limit=20,
)

# Real-time recommendation with business rules
results = client.recommend(
    collection_name="products",
    positive=[last_viewed_id, last_purchased_id],
    negative=[returned_item_id],
    query_filter=Filter(must=[
        FieldCondition("in_stock", match=MatchValue(True)),
        FieldCondition("margin", range=Range(gte=0.25)),
    ]),
    strategy=RecommendStrategy.BEST_SCORE,
    limit=12,
)

# Update user vector on interaction (real-time)
client.set_payload(
    "users",
    payload={"last_active": datetime.now().isoformat()},
    points=[user_id],
)