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from qdrant_client import QdrantClient
from qdrant_client.models import Prefetch, FusionQuery, Fusion
def query_keywords_search(query: str, client: QdrantClient, collection_name: str, sparse_embeddings):
return client.query_points(
collection_name=collection_name,
prefetch=Prefetch(query=sparse_embeddings, using='title-sparse', limit=25),
query=FusionQuery(fusion=Fusion.RRF),
with_vectors=False,
with_payload=True,
limit=1
)
def query_hybrid_search(query: str, client: QdrantClient, collection_name: str, dense_embeddings, sparse_embeddings):
return client.query_points(
collection_name=collection_name,
prefetch=[
Prefetch(query=sparse_embeddings, using="text-sparse", limit=25),
Prefetch(query=dense_embeddings[0], using="text-dense", limit=25)
],
query=FusionQuery(fusion=Fusion.RRF),
with_vectors=False,
with_payload=True,
limit=10,
score_threshold=0.95
) |