Hi there! We're trying to make use of semantic search embeddings with the VueInstantSearch copmonents and have an Autocomplete component that makes the following search. The autocomplete component correctly returns semantic results, but the same configuration for the results component does not. I suspect this is due to the addition of the filter_by configuration required for faceting.

{
  "searches": [
    {
      "query_by": "name, sku, embedding",
      "collection": "products",
      "q": "*",
      "filter_by": "name:lemon",
      "page": 1,
      "per_page": 24
    }
  ]
}

and a results faceting component that makes the following search

{"searches":[{"query_by":"name, sku, embedding","vector_query":"embedding:([], k: 4, distance_threshold: 0.25)","collection":"products","q":"lemon","page":1},

but they're somehow both using the same

collectionSpecificSearchParameters

collectionSpecificSearchParameters: {
    products: {
      query_by: "name, sku, embedding",
      vector_query: "embedding:([], k: 4, distance_threshold: 0.25)"
    },
    categories: {
      query_by: "name",
    },
    recommended_content: {
      query_by: "title",
    },
    popular_queries: {
      query_by: "q",
      highlight_full_fields: '',
    },
  },

Does this imply that I can't do a text search using embeddings and can only do it in a non-filtering q:"*" scenario?