Neural query
- Request body fields
  - Example request

Neural query

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

Request body 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. Only one variable, either `k`, `min_score`, or `max_distance`, can be specified. If a variable is not specified, the default is `k` with a value of `10`.
`min_score`	Float	Optional	The minimum score threshold for the search results. Only one variable, either `k`, `min_score`, or `max_distance`, can be specified. For more information, see k-NN radial search.
`max_distance`	Float	Optional	The maximum distance threshold for the search results. Only one variable, either `k`, `min_score`, or `max_distance`, can be specified. For more information, see k-NN radial search.
`filter`	Object	Optional	A query that can be used to reduce the number of documents considered. For more information about filter usage, see k-NN search with filters. Important: Filter can only be used with the `faiss` or `lucene` engines.
`method_parameters`	Object	Optional	Parameters passed to the k-NN index during search. See Additional query parameters.
`rescore`	Object	Optional	Parameters for configuring rescoring functionality for k-NN indexes built using quantization. See Rescoring.

Example request

The following example shows a search with a k value of 100 and a filter that includes a range query and a term query:

GET /my-nlp-index/_search
{
  "query": {
    "neural": {
      "passage_embedding": {
        "query_text": "Hi world",
        "query_image": "iVBORw0KGgoAAAAN...",
        "k": 100,
        "filter": {
          "bool": {
            "must": [
              {
                "range": {
                  "rating": {
                    "gte": 8,
                    "lte": 10
                  }
                }
              },
              {
                "term": {
                  "parking": "true"
                }
              }
            ]
          }
        }
      }
    }
  }
}

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The following search query includes a k-NN radial search min_score of 0.95 and a filter that includes a range query and a term query:

GET /my-nlp-index/_search
{
  "query": {
    "neural": {
      "passage_embedding": {
        "query_text": "Hi world",
        "query_image": "iVBORw0KGgoAAAAN...",
        "min_score": 0.95,
        "filter": {
          "bool": {
            "must": [
              {
                "range": {
                  "rating": {
                    "gte": 8,
                    "lte": 10
                  }
                }
              },
              {
                "term": {
                  "parking": "true"
                }
              }
            ]
          }
        }
      }
    }
  }
}

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The following search query includes a k-NN radial search max_distance of 10 and a filter that includes a range query and a term query:

GET /my-nlp-index/_search
{
  "query": {
    "neural": {
      "passage_embedding": {
        "query_text": "Hi world",
        "query_image": "iVBORw0KGgoAAAAN...",
        "max_distance": 10,
        "filter": {
          "bool": {
            "must": [
              {
                "range": {
                  "rating": {
                    "gte": 8,
                    "lte": 10
                  }
                }
              },
              {
                "term": {
                  "parking": "true"
                }
              }
            ]
          }
        }
      }
    }
  }
}

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