Worked on the redis/redis-vl-python repository to enhance the reliability of vector similarity queries by refining the VectorQuery API. Focused on backend development using Python, the developer removed the epsilon parameter and its related methods from VectorQuery, addressing parsing errors that occurred when non-range query attributes were sent to Redis. This cleanup aligned VectorQuery’s behavior with VectorRangeQuery, ensuring compatibility and reducing error-prone code paths. Through careful unit testing and code simplification, the changes improved the stability and predictability of vector searches, making query construction more straightforward and minimizing the risk of Redis parsing errors in the integration stack.