Get inference API
editGet inference API
editThis functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
Retrieves inference endpoint information.
The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, or Hugging Face. For built-in models and models uploaded through Eland, the inference APIs offer an alternative way to use and manage trained models. However, if you do not plan to use the inference APIs to use these models or if you want to use non-NLP models, use the Machine learning trained model APIs.
Request
editGET /_inference/_all
GET /_inference/<inference_id>
GET /_inference/<task_type>/_all
GET /_inference/<task_type>/<inference_id>
Prerequisites
edit-
Requires the
managecluster privilege.
Description
editYou can get information in a single API request for:
- a single inference endpoint by providing the task type and the inference ID,
- all of the inference endpoints for a certain task type by providing the task type and a wildcard expression,
- all of the inference endpoints by using a wildcard expression.
Path parameters
edit-
<inference_id> - (Optional, string) The unique identifier of the inference endpoint.
-
<task_type> - (Optional, string) The type of inference task that the model performs.
Examples
editThe following API call retrieves information about the my-elser-model inference
model that can perform sparse_embedding tasks.
resp = client.inference.get_model(
task_type="sparse_embedding",
inference_id="my-elser-model",
)
print(resp)
response = client.inference.get_model( task_type: 'sparse_embedding', model_id: 'my-elser-model' ) puts response
GET _inference/sparse_embedding/my-elser-model
The API returns the following response:
{
"inference_id": "my-elser-model",
"task_type": "sparse_embedding",
"service": "elser",
"service_settings": {
"num_allocations": 1,
"num_threads": 1
},
"task_settings": {}
}