Neural query
- Request fields
  - Example request

Neural query

Use the neural query for vector field search in neural search.

Request fields

Include the following request fields in the neural query:

"neural": {
  "<vector_field>": {
    "query_text": "<query_text>",
    "query_image": "<image_binary>",
    "model_id": "<model_id>",
    "k": 100
  }
}

The top-level vector_field specifies the vector field against which to run a search query. The following table lists the other neural query fields.

Field	Data type	Required/Optional	Description
`query_text`	String	Optional	The query text from which to generate vector embeddings. You must specify at least one `query_text` or `query_image`.
`query_image`	String	Optional	A base-64 encoded string that corresponds to the query image from which to generate vector embeddings. You must specify at least one `query_text` or `query_image`.
`model_id`	String	Required if the default model ID is not set. For more information, see Setting a default model on an index or field.	The ID of the model that will be used to generate vector embeddings from the query text. The model must be deployed in OpenSearch before it can be used in neural search. For more information, see Using custom models within OpenSearch and Neural search.
`k`	Integer	Optional	The number of results returned by the k-NN search. Default is 10.

Example request

GET /my-nlp-index/_search
{
  "query": {
    "neural": {
      "passage_embedding": {
        "query_text": "Hi world",
        "query_image": "iVBORw0KGgoAAAAN...",
        "k": 100
      }
    }
  }
}

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