mirror of
https://github.com/elastic/elasticsearch.git
synced 2025-04-25 07:37:19 -04:00
110 lines
2.7 KiB
Text
110 lines
2.7 KiB
Text
[role="xpack"]
|
|
[[post-inference-api]]
|
|
=== Perform inference API
|
|
|
|
experimental[]
|
|
|
|
Performs an inference task on an input text by using an {infer} model.
|
|
|
|
IMPORTANT: The {infer} APIs enable you to use certain services, such as ELSER,
|
|
OpenAI, or Hugging Face, in your cluster. This is not the same feature that you
|
|
can use on an ML node with custom {ml} models. If you want to train and use your
|
|
own model, use the <<ml-df-trained-models-apis>>.
|
|
|
|
|
|
[discrete]
|
|
[[post-inference-api-request]]
|
|
==== {api-request-title}
|
|
|
|
`POST /_inference/<inference_id>`
|
|
|
|
`POST /_inference/<task_type>/<inference_id>`
|
|
|
|
|
|
[discrete]
|
|
[[post-inference-api-prereqs]]
|
|
==== {api-prereq-title}
|
|
|
|
* Requires the `monitor_inference` <<privileges-list-cluster,cluster privilege>>
|
|
(the built-in `inference_admin` and `inference_user` roles grant this privilege)
|
|
|
|
[discrete]
|
|
[[post-inference-api-desc]]
|
|
==== {api-description-title}
|
|
|
|
The perform {infer} API enables you to use {ml} models to perform specific tasks
|
|
on data that you provide as an input. The API returns a response with the
|
|
resutls of the tasks. The {infer} model you use can perform one specific task
|
|
that has been defined when the model was created with the <<put-inference-api>>.
|
|
|
|
|
|
[discrete]
|
|
[[post-inference-api-path-params]]
|
|
==== {api-path-parms-title}
|
|
|
|
`<inference_id>`::
|
|
(Required, string)
|
|
The unique identifier of the {infer} endpoint.
|
|
|
|
|
|
`<task_type>`::
|
|
(Optional, string)
|
|
The type of {infer} task that the model performs.
|
|
|
|
|
|
[discrete]
|
|
[[post-inference-api-request-body]]
|
|
== {api-request-body-title}
|
|
|
|
`input`::
|
|
(Required, array of strings)
|
|
The text on which you want to perform the {infer} task.
|
|
`input` can be a single string or an array.
|
|
|
|
|
|
[discrete]
|
|
[[post-inference-api-example]]
|
|
==== {api-examples-title}
|
|
|
|
The following example performs sparse embedding on the example sentence.
|
|
|
|
|
|
[source,console]
|
|
------------------------------------------------------------
|
|
POST _inference/sparse_embedding/my-elser-model
|
|
{
|
|
"input": "The sky above the port was the color of television tuned to a dead channel."
|
|
}
|
|
------------------------------------------------------------
|
|
// TEST[skip:TBD]
|
|
|
|
|
|
The API returns the following response:
|
|
|
|
|
|
[source,console-result]
|
|
------------------------------------------------------------
|
|
{
|
|
"sparse_embedding": [
|
|
{
|
|
"port": 2.1259406,
|
|
"sky": 1.7073475,
|
|
"color": 1.6922266,
|
|
"dead": 1.6247464,
|
|
"television": 1.3525393,
|
|
"above": 1.2425821,
|
|
"tuned": 1.1440028,
|
|
"colors": 1.1218185,
|
|
"tv": 1.0111054,
|
|
"ports": 1.0067928,
|
|
"poem": 1.0042328,
|
|
"channel": 0.99471164,
|
|
"tune": 0.96235967,
|
|
"scene": 0.9020516,
|
|
(...)
|
|
},
|
|
(...)
|
|
]
|
|
}
|
|
------------------------------------------------------------
|
|
// NOTCONSOLE
|