Hello everyone, I'm working with typesense search semantic feature on my platform. For that, I use an embedding model to read some fields in each document. This feat includes a match score for every row; the issue was that typesense only suggested one row. I tried a lot of configurations to get a minimum of 5 suggestions sorted by vector match. Did anyone try anything similar or know the fix? Thanks a lot

Could you share a curl request of the search query you're sending Typesense?

hi Jason, my search parameters is this: final searchParameters = { 'q': query, 'query_by': 'embedding', 'group_by': 'job_group_dominant', 'exclude_fields': 'embedding', 'per_page': '10', 'group_limit': '1', }; thanks for the support