Weaviate 1.27
introduced the new filtering strategy based on the ACORN
paper.
According to our internal tests, the ACORN algorithm generally improves the filtered vector search performances, with the most significant improvements in negatively correlated filtered searches.
We are excited for you to try it out! If you have the Python client, you can activate it like so:
from weaviate.classes.config import Configure, Property, DataType, VectorDistances, VectorFilterStrategy
client.collections.create(
"Article",
# Additional configuration not shown
vector_index_config=Configure.VectorIndex.hnsw(
quantizer=Configure.VectorIndex.Quantizer.bq(),
ef_construction=300,
distance_metric=VectorDistances.COSINE,
filter_strategy=VectorFilterStrategy.ACORN # (Available from Weaviate v1.27.0)
),
)
Read more in our 1.27
release blog (Blog | Weaviate) that will be posted later today
Try it out and let us know what you think!