COMPLETION

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The COMPLETION command allows you to send prompts and context to a Large Language Model (LLM) directly within your ES|QL queries, to perform text generation tasks.

Syntax

COMPLETION [column =] prompt WITH { "inference_id" : "my_inference_endpoint" }

COMPLETION [column =] prompt WITH my_inference_endpoint

Parameters

column

(Optional) The name of the output column containing the LLM's response. If not specified, the results will be stored in a column named completion. If the specified column already exists, it will be overwritten with the new results.

prompt

The input text or expression used to prompt the LLM. This can be a string literal or a reference to a column containing text.

my_inference_endpoint

The ID of the inference endpoint to use for the task. The inference endpoint must be configured with the completion task type.

Description

The COMPLETION command provides a general-purpose interface for text generation tasks using a Large Language Model (LLM) in ES|QL.

COMPLETION supports a wide range of text generation tasks. Depending on your prompt and the model you use, you can perform arbitrary text generation tasks including:

• Question answering
• Summarization
• Translation
• Content rewriting
• Creative generation

Requirements

To use this command, you must deploy your LLM model in Elasticsearch as an inference endpoint with the task type completion.

COMPLETION commands may time out when processing large datasets or complex prompts. The default timeout is 10 minutes, but you can increase this limit if necessary.

How you increase the timeout depends on your deployment type:

If you don't want to increase the timeout limit, try the following:

• Reduce data volume with LIMIT or more selective filters before the COMPLETION command
• Split complex operations into multiple simpler queries
• Configure your HTTP client's response timeout (Refer to HTTP client configuration)

Examples

Use the default column name (results stored in completion column):

ROW question = "What is Elasticsearch?"
| COMPLETION question WITH { "inference_id" : "my_inference_endpoint" }
| KEEP question, completion

Specify the output column (results stored in answer column):

ROW question = "What is Elasticsearch?"
| COMPLETION answer = question WITH { "inference_id" : "my_inference_endpoint" }
| KEEP question, answer

Summarize the top 10 highest-rated movies using a prompt:

FROM movies
| SORT rating DESC
| LIMIT 10
| EVAL prompt = CONCAT(
   "Summarize this movie using the following information: \n",
   "Title: ", title, "\n",
   "Synopsis: ", synopsis, "\n",
   "Actors: ", MV_CONCAT(actors, ", "), "\n",
  )
| COMPLETION summary = prompt WITH { "inference_id" : "my_inference_endpoint" }
| KEEP title, summary, rating