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"
}
}
]
}
}
}
}
}
}
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"
}
}
]
}
}
}
}
}
}
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"
}
}
]
}
}
}
}
}
}