* Restructuring TOC Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Resolve merge conflicts Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * More foundational rewrites of ML Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * TOC restructure Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Rename and rewrite search pages and add keyword search Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Small wording change Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Small wording change Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Updated response Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Apply suggestions from code review Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> * Small rewording Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Move neural search to top of vector search list Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Change terminology Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Reorganize search methods list Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Rename links Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * More link renames Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> * Apply suggestions from code review Co-authored-by: Nathan Bower <nbower@amazon.com> Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> * Implemented editorial comments Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> --------- Signed-off-by: Fanit Kolchina <kolchfa@amazon.com> Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com> Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Co-authored-by: Nathan Bower <nbower@amazon.com>
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layout | title | parent | grand_parent | nav_order |
---|---|---|---|---|
default | Neural | Specialized queries | Query DSL | 50 |
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
}
}
}
}
{% include copy-curl.html %}