elasticsearch/docs/reference/inference/service-openai.asciidoc

[[infer-service-openai]]
=== OpenAI {infer} service

Creates an {infer} endpoint to perform an {infer} task with the `openai` service.


[discrete]
[[infer-service-openai-api-request]]
==== {api-request-title}

`PUT /_inference/<task_type>/<inference_id>`

[discrete]
[[infer-service-openai-api-path-params]]
==== {api-path-parms-title}

`<inference_id>`::
(Required, string)
include::inference-shared.asciidoc[tag=inference-id]

`<task_type>`::
(Required, string)
include::inference-shared.asciidoc[tag=task-type]
+
--
Available task types:

* `completion`,
* `text_embedding`.
--

[discrete]
[[infer-service-openai-api-request-body]]
==== {api-request-body-title}

`service`::
(Required, string)
The type of service supported for the specified task type. In this case, 
`openai`.

`service_settings`::
(Required, object)
include::inference-shared.asciidoc[tag=service-settings]
+
--
These settings are specific to the `openai` service.
--

`api_key`:::
(Required, string)
A valid API key of your OpenAI account.
You can find your OpenAI API keys in your OpenAI account under the
https://platform.openai.com/api-keys[API keys section].
+
--
include::inference-shared.asciidoc[tag=api-key-admonition]
--

`model_id`:::
(Required, string)
The name of the model to use for the {infer} task.
Refer to the
https://platform.openai.com/docs/guides/embeddings/what-are-embeddings[OpenAI documentation]
for the list of available text embedding models.

`organization_id`:::
(Optional, string)
The unique identifier of your organization.
You can find the Organization ID in your OpenAI account under
https://platform.openai.com/account/organization[**Settings** > **Organizations**].

`url`:::
(Optional, string)
The URL endpoint to use for the requests.
Can be changed for testing purposes.
Defaults to `https://api.openai.com/v1/embeddings`.

`rate_limit`:::
(Optional, object)
The `openai` service sets a default number of requests allowed per minute depending on the task type.
For `text_embedding` it is set to `3000`.
For `completion` it is set to `500`.
This helps to minimize the number of rate limit errors returned from OpenAI.
To modify this, set the `requests_per_minute` setting of this object in your service settings:
+
--
include::inference-shared.asciidoc[tag=request-per-minute-example]

More information about the rate limits for OpenAI can be found in your https://platform.openai.com/account/limits[Account limits].
--

`task_settings`::
(Optional, object)
include::inference-shared.asciidoc[tag=task-settings]
+
.`task_settings` for the `completion` task type
[%collapsible%closed]
=====
`user`:::
(Optional, string)
Specifies the user issuing the request, which can be used for abuse detection.
=====
+
.`task_settings` for the `text_embedding` task type
[%collapsible%closed]
=====
`user`:::
(optional, string)
Specifies the user issuing the request, which can be used for abuse detection.
=====


[discrete]
[[inference-example-openai]]
==== OpenAI service example

The following example shows how to create an {infer} endpoint called
`openai-embeddings` to perform a `text_embedding` task type.

[source,console]
------------------------------------------------------------
PUT _inference/text_embedding/openai-embeddings
{
    "service": "openai",
    "service_settings": {
        "api_key": "<api_key>",
        "model_id": "text-embedding-ada-002"
    }
}
------------------------------------------------------------
// TEST[skip:TBD]

The next example shows how to create an {infer} endpoint called
`openai-completion` to perform a `completion` task type.

[source,console]
------------------------------------------------------------
PUT _inference/completion/openai-completion
{
    "service": "openai",
    "service_settings": {
        "api_key": "<api_key>",
        "model_id": "gpt-3.5-turbo"
    }
}
------------------------------------------------------------
// TEST[skip:TBD]