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+## `COMPLETION` [esql-completion]
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+
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+```yaml {applies_to}
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+serverless: preview
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+stack: preview 9.1.0
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+```
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+
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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.
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+
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+**Syntax**
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+
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+```esql
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+COMPLETION [column =] prompt WITH inference_id
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+```
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+
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+**Parameters**
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+
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+`column`
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+: (Optional) The name of the output column containing the LLM's response.
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+ If not specified, the results will be stored in a column named `completion`.
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+ If the specified column already exists, it will be overwritten with the new results.
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+
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+`prompt`
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+: The input text or expression used to prompt the LLM.
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+ This can be a string literal or a reference to a column containing text.
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+
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+`inference_id`
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+: The ID of the [inference endpoint](docs-content://explore-analyze/elastic-inference/inference-api.md) to use for the task.
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+ The inference endpoint must be configured with the `completion` task type.
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+
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+**Description**
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+
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+The `COMPLETION` command provides a general-purpose interface for
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+text generation tasks using a Large Language Model (LLM) in ES|QL.
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+
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+`COMPLETION` supports a wide range of text generation tasks. Depending on your
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+prompt and the model you use, you can perform arbitrary text generation tasks
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+including:
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+
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+- Question answering
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+- Summarization
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+- Translation
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+- Content rewriting
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+- Creative generation
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+
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+**Requirements**
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+
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+To use this command, you must deploy your LLM model in Elasticsearch as
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+an [≈inference endpoint](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-put) with the
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+task type `completion`.
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+
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+**Examples**
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+
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+Use the default column name (results stored in `completion` column):
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+
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+```esql
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+ROW question = "What is Elasticsearch?"
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+| COMPLETION question WITH test_completion_model
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+| KEEP question, completion
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+```
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+
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+| question:keyword | completion:keyword |
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+|------------------------|-------------------------------------------|
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+| What is Elasticsearch? | A distributed search and analytics engine |
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+
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+Specify the output column (results stored in `answer` column):
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+
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+```esql
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+ROW question = "What is Elasticsearch?"
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+| COMPLETION answer = question WITH test_completion_model
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+| KEEP question, answer
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+```
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+
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+| question:keyword | answer:keyword |
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+| --- | --- |
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+| What is Elasticsearch? | A distributed search and analytics engine |
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+
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+Summarize the top 10 highest-rated movies using a prompt:
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+
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+```esql
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+FROM movies
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+| SORT rating DESC
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+| LIMIT 10
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+| EVAL prompt = CONCAT(
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+ "Summarize this movie using the following information: \n",
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+ "Title: ", title, "\n",
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+ "Synopsis: ", synopsis, "\n",
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+ "Actors: ", MV_CONCAT(actors, ", "), "\n",
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+ )
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+| COMPLETION summary = prompt WITH test_completion_model
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+| KEEP title, summary, rating
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+```
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+
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+
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+| title:keyword | summary:keyword | rating:double |
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+| --- | --- | --- |
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+| The Shawshank Redemption | A tale of hope and redemption in prison. | 9.3 |
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+| The Godfather | A mafia family's rise and fall. | 9.2 |
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+| The Dark Knight | Batman battles the Joker in Gotham. | 9.0 |
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+| Pulp Fiction | Interconnected crime stories with dark humor. | 8.9 |
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+| Fight Club | A man starts an underground fight club. | 8.8 |
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+| Inception | A thief steals secrets through dreams. | 8.8 |
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+| The Matrix | A hacker discovers reality is a simulation. | 8.7 |
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+| Parasite | Class conflict between two families. | 8.6 |
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+| Interstellar | A team explores space to save humanity. | 8.6 |
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+| The Prestige | Rival magicians engage in dangerous competition. | 8.5 |
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Aurélien FOUCRET