semantic query

A semantic query can be used to search text fields with semantic search enabled. Unlike the knn query, the semantic query accepts text query string and computes embeddings. So for a field title defined as:

inference:
  embedding:
    e5-small:
      model: intfloat/e5-small-v2 # perform local ONNX inference
schema:
  my-index:
    fields:
      title:
        type: text
        search:
          semantic:           # build an a-kNN HNSW index
            model: e5-small   # use this model for embeddings

Such a field can be searched with the semantic query:

{
  "query": {
    "semantic": {
      "field": "title",
      "query": "cookies",
      "k": 20 
    }
  }
}

Or with a shorter form:

{
  "query": {
    "semantic": {"title": "cookies"}
  }
}

Where the fields are:

• field: a text field with semantic search enabled in the index mapping.
• query: a text query. The query is not analyzed and fed into the embedding model as-is.
• k: an optional parameter of how many neighbor documents to fetch. By default, equals to the request.size field.

For a case when you already have a pre-embedded query and want to search over the embedding vector directly skipping the inference, see the knn query.