Background with more context on my problem Yesterday I decided to send my ~24,000 products from Supabase to OAI's Embedding API as batches using the model *`text-embedding-3-small`*that has 1536 dimensions. Once I retrieved the embeddings, I combined them with my product information from Supabase and created a new collection in Typesense with this upload schema code for the embedding field:

{ 
      name: 'embedding', 
      type: 'float[]',
      num_dim: 1536, // model uses 1536 dimensions
      optional: true
    }

When I view my current schema in Typesense, I see:

{
      "facet": false,
      "hnsw_params": {
        "M": 16,
        "ef_construction": 200
      },
      "index": true,
      "infix": false,
      "locale": "",
      "name": "embedding",
      "num_dim": 1536,
      "optional": true,
      "sort": false,
      "stem": false,
      "store": true,
      "type": "float[]",
      "vec_dist": "cosine"
    },

Current Testing/ Debugging In my current process that isn't working, when a user inputs a query, I make a call to OAI with the

text-embedding-3-small

model to get the vector query which I insert into the search query object. Every time I've sent this request or similar (see below), I keep getting 0 products returned.

Complete Typesense Request:
{
  "searches": [
    {
      "collection": "product-embeddings-v2",
      "q": "*",
      "vector_query": "embedding:([ {vector query from OAI} ], k:200)",
      "exclude_fields": "embedding",
      "sort_by": "averageRating:desc",
      "per_page": 24
    }
  ]
}

I then decided to query the products themselves directly to see what fields they have and I do not see

embedding

being returned as a field which is probably why I'm getting 0 products when attempting a vector_query search. Does anyone know what might be happening here? Thanks!