Stream inference API
editStream inference API
editStreams a chat completion response.
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.
Request
editPOST /_inference/<inference_id>/_stream
POST /_inference/<task_type>/<inference_id>/_stream
Prerequisites
edit-
Requires the
monitor_inference
cluster privilege (the built-ininference_admin
andinference_user
roles grant this privilege) - You must use a client that supports streaming.
Description
editThe stream inference API enables real-time responses for completion tasks by delivering answers incrementally, reducing response times during computation.
It only works with the completion
and chat_completion
task types.
The Chat completion inference API and the Stream inference API differ in their response structure and capabilities.
The Chat completion inference API provides more comprehensive customization options through more fields and function calling support.
If you use the openai
service or the elastic
service, use the Chat completion inference API.
For more information on how to use the chat_completion
task type, please refer to the chat completion documentation.
Path parameters
edit-
<inference_id>
- (Required, string) The unique identifier of the inference endpoint.
-
<task_type>
- (Optional, string) The type of inference task that the model performs.
Request body
edit-
input
-
(Required, string or array of strings) The text on which you want to perform the inference task.
input
can be a single string or an array.Inference endpoints for the
completion
task type currently only support a single string as input.
Examples
editThe following example performs a completion on the example question with streaming.
resp = client.inference.stream_completion( inference_id="openai-completion", input="What is Elastic?", ) print(resp)
const response = await client.inference.streamInference({ task_type: "completion", inference_id: "openai-completion", input: "What is Elastic?", }); console.log(response);
POST _inference/completion/openai-completion/_stream { "input": "What is Elastic?" }
The API returns the following response:
event: message data: { "completion":[{ "delta":"Elastic" }] } event: message data: { "completion":[{ "delta":" is" }, { "delta":" a" } ] } event: message data: { "completion":[{ "delta":" software" }, { "delta":" company" }] } (...)