Update an inference endpoint
Added in 8.17.0
Modify task_settings
, secrets (within service_settings
), or num_allocations
for an inference endpoint, depending on the specific endpoint service and task_type
.
IMPORTANT: The inference APIs enable you to use certain services, such as built-in machine learning models (ELSER, E5), models uploaded through Eland, Cohere, OpenAI, Azure, Google AI Studio, Google Vertex AI, Anthropic, Watsonx.ai, 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.
Path parameters
-
task_type
string Required The type of inference task that the model performs.
Values are
sparse_embedding
,text_embedding
,rerank
, orcompletion
. -
inference_id
string Required The unique identifier of the inference endpoint.
Body
Required
-
chunking_settings
object Additional properties are allowed.
-
service
string Required The service type
-
service_settings
object Required Additional properties are allowed.
-
task_settings
object Additional properties are allowed.
curl \
--request POST http://api.example.com/_inference/{task_type}/{inference_id}/_update \
--header "Authorization: $API_KEY" \
--header "Content-Type: application/json" \
--data '{"":{"max_chunk_size":42.0,"overlap":42.0,"sentence_overlap":42.0,"strategy":"string"},"service":"string","service_settings":{},"task_settings":{}}'
{
"": {
"max_chunk_size": 42.0,
"overlap": 42.0,
"sentence_overlap": 42.0,
"strategy": "string"
},
"service": "string",
"service_settings": {},
"task_settings": {}
}
{
"": {
"max_chunk_size": 42.0,
"overlap": 42.0,
"sentence_overlap": 42.0,
"strategy": "string"
},
"service": "string",
"service_settings": {},
"task_settings": {},
"inference_id": "string",
"task_type": "sparse_embedding"
}