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Redis Stack for Application Modernization
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To understand what range queries are in the context of VSS, an edge case would be searching for two element vectors that model the coordinates of points in a bi-dimensional Cartesian plane. Another example would be geographical locations expressed with longitude and latitude. In these cases, a range query that uses VSS would find closer points in this bi-dimensional space, so within the desired distance from the query vector. Thinking of multi-dimensional spaces, we can imagine the most different use cases. Using VSS range queries, we want to discover relevant content within a predefined similarity range, instead of looking up the KNN similar vectors.
We can customize the example we’ve considered so far and rewrite the search operation as follows:
q = Query("@embedding:[VECTOR_RANGE $radius $vec]=>{$YIELD_DISTANCE_AS: score}") \ .sort_by("score") \ .return_field("score...