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Fix score_threshold applied backwards for Recommend/Discover/Context on Euclidean/Manhattan collections #1374

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Fix score_threshold applied backwards for Recommend/Discover/Context on Euclidean/Manhattan collections #1374

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13 changes: 10 additions & 3 deletions qdrant_client/local/local_collection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -697,7 +697,12 @@ def search(

required_order = distance_to_order(distance)

if required_order == DistanceOrder.BIGGER_IS_BETTER or isinstance(
# Recommend (best_score/sum_scores), Discover, and Context queries always
# compute a sigmoid-based synthetic score where bigger is always better,
# regardless of the collection's underlying distance metric. This override
# must be applied consistently everywhere required_order is used for these
# query types - both for sort direction and for score_threshold comparison.
bigger_is_better = required_order == DistanceOrder.BIGGER_IS_BETTER or isinstance(
query_vector,
(
DiscoveryQuery,
Expand All @@ -707,7 +712,9 @@ def search(
MultiContextQuery,
MultiRecoQuery,
), # sparse structures are not required, sparse always uses DOT
):
)

if bigger_is_better:
order = np.argsort(scores)[::-1]
else:
order = np.argsort(scores)
Expand All @@ -727,7 +734,7 @@ def search(
point_id = self.ids_inv[idx]

if score_threshold is not None:
if required_order == DistanceOrder.BIGGER_IS_BETTER:
if bigger_is_better:
if score < score_threshold:
break
else:
Expand Down