Geo-filtered vector search
I would store the item's latitude and longitude in a geo payload field and combine a radius filter with the vector query. The vector query provides similarity ranking, while the geo filter constrains eligible points to the required geographic radius.
This is different from treating latitude and longitude as ordinary numeric fields. Qdrant has geo-specific payload conditions for radius and bounding-box searches, which understand geographic coordinates.
The trade-off is radius precision versus query cost and product requirements. A bounding box can be useful as a coarse prefilter, while a radius represents the actual distance requirement. I would use the geo condition directly when the 5 km boundary is part of the correctness requirement.
A common mistake is calculating distance in application code after retrieving nearest vectors. That recreates the post-filtering problem and can return too few results. The exact geo query syntax is version-dependent, so I would use the SDK/API schema for the deployed Qdrant version.
Store coordinates in a Qdrant geo payload field
Combine geo_radius with vector similarity when both constraints matter
Use geo-specific conditions rather than ordinary numeric comparisons for coordinates
Avoid retrieving a small global top-k and applying geographic filtering afterward
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