Hi Typesense team, I’m trying to implement a user-based personalized search, similar to Algolia’s personalization, but in Typesense. The personalization is primarily tag-based. For example: • If a user has a preference for the cuisine tag “Italian” and a dietary preference for “chicken”, • When the user searches for “pasta”, the results should prioritize dishes like chicken alfredo. This works reasonably well, but there are inconsistencies: • For instance, when searching for “cake”, the system sometimes surfaces unrelated items like pancakes with chicken. The issue seems related to query intent classification. To address this, I’m experimenting with: • Using Qdrant (vector DB) to classify the intent of the query. • Dynamically parsing a sorting string in Typesense that adjusts the weightage of certain tags. I know you recommend using the StarSpace model for personalization, but I’m not aiming for a heavy ML approach. Could you recommend a stable strategy for achieving consistent, tag-based personalization in Typesense without going full ML? Thanks,