Data stream

Learn more about data streams

Get data streams Added in 7.9.0

GET /_data_stream/{name}
Api key auth Basic auth Bearer auth

Get information about one or more data streams.

Path parameters

  • name string | array[string] Required

    Comma-separated list of data stream names used to limit the request. Wildcard (*) expressions are supported. If omitted, all data streams are returned.

Query parameters

  • expand_wildcards string | array[string]

    Type of data stream that wildcard patterns can match. Supports comma-separated values, such as open,hidden.

    Supported values include:

    • all: Match any data stream or index, including hidden ones.
    • open: Match open, non-hidden indices. Also matches any non-hidden data stream.
    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.
    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.
    • none: Wildcard expressions are not accepted.

    Values are all, open, closed, hidden, or none.

  • include_defaults boolean

    If true, returns all relevant default configurations for the index template.

  • master_timeout string

    Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • verbose boolean

    Whether the maximum timestamp for each data stream should be calculated and returned.

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • data_streams array[object] Required
      Hide data_streams attributes Show data_streams attributes object
      • _meta object
        Hide _meta attribute Show _meta attribute object
        • * object Additional properties
      • allow_custom_routing boolean

        If true, the data stream allows custom routing on write request.

      • failure_store object
        Hide failure_store attributes Show failure_store attributes object
      • generation number Required

        Current generation for the data stream. This number acts as a cumulative count of the stream’s rollovers, starting at 1.

      • hidden boolean Required

        If true, the data stream is hidden.

      • ilm_policy string
      • next_generation_managed_by string Required

        Values are Index Lifecycle Management, Data stream lifecycle, or Unmanaged.

      • prefer_ilm boolean Required

        Indicates if ILM should take precedence over DSL in case both are configured to managed this data stream.

      • indices array[object] Required

        Array of objects containing information about the data stream’s backing indices. The last item in this array contains information about the stream’s current write index.

        Hide indices attributes Show indices attributes object
      • lifecycle object
        Hide lifecycle attributes Show lifecycle attributes object
      • name string Required
      • replicated boolean

        If true, the data stream is created and managed by cross-cluster replication and the local cluster can not write into this data stream or change its mappings.

      • rollover_on_write boolean Required

        If true, the next write to this data stream will trigger a rollover first and the document will be indexed in the new backing index. If the rollover fails the indexing request will fail too.

      • status string Required

        Values are green, GREEN, yellow, YELLOW, red, or RED.

      • system boolean

        If true, the data stream is created and managed by an Elastic stack component and cannot be modified through normal user interaction.

      • template string Required
      • timestamp_field object Required
        Hide timestamp_field attribute Show timestamp_field attribute object
        • name string Required

          Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.
GET /_data_stream/{name} 
curl \
 --request GET 'http://api.example.com/_data_stream/{name}' \
 --header "Authorization: $API_KEY"
Response examples (200)
A successful response for retrieving information about a data stream. 
{
  "data_streams": [
    {
      "name": "my-data-stream",
      "timestamp_field": {
        "name": "@timestamp"
      },
      "indices": [
        {
          "index_name": ".ds-my-data-stream-2099.03.07-000001",
          "index_uuid": "xCEhwsp8Tey0-FLNFYVwSg",
          "prefer_ilm": true,
          "ilm_policy": "my-lifecycle-policy",
          "managed_by": "Index Lifecycle Management"
        },
        {
          "index_name": ".ds-my-data-stream-2099.03.08-000002",
          "index_uuid": "PA_JquKGSiKcAKBA8DJ5gw",
          "prefer_ilm": true,
          "ilm_policy": "my-lifecycle-policy",
          "managed_by": "Index Lifecycle Management"
        }
      ],
      "generation": 2,
      "_meta": {
        "my-meta-field": "foo"
      },
      "status": "GREEN",
      "next_generation_managed_by": "Index Lifecycle Management",
      "prefer_ilm": true,
      "template": "my-index-template",
      "ilm_policy": "my-lifecycle-policy",
      "hidden": false,
      "system": false,
      "allow_custom_routing": false,
      "replicated": false,
      "rollover_on_write": false
    },
    {
      "name": "my-data-stream-two",
      "timestamp_field": {
        "name": "@timestamp"
      },
      "indices": [
        {
          "index_name": ".ds-my-data-stream-two-2099.03.08-000001",
          "index_uuid": "3liBu2SYS5axasRt6fUIpA",
          "prefer_ilm": true,
          "ilm_policy": "my-lifecycle-policy",
          "managed_by": "Index Lifecycle Management"
        }
      ],
      "generation": 1,
      "_meta": {
        "my-meta-field": "foo"
      },
      "status": "YELLOW",
      "next_generation_managed_by": "Index Lifecycle Management",
      "prefer_ilm": true,
      "template": "my-index-template",
      "ilm_policy": "my-lifecycle-policy",
      "hidden": false,
      "system": false,
      "allow_custom_routing": false,
      "replicated": false,
      "rollover_on_write": false
    }
  ]
}

Create a data stream Added in 7.9.0

PUT /_data_stream/{name}
Api key auth Basic auth Bearer auth

You must have a matching index template with data stream enabled.

Path parameters

  • name string Required

    Name of the data stream, which must meet the following criteria: Lowercase only; Cannot include \, /, *, ?, ", <, >, |, ,, #, :, or a space character; Cannot start with -, _, +, or .ds-; Cannot be . or ..; Cannot be longer than 255 bytes. Multi-byte characters count towards this limit faster.

Query parameters

  • master_timeout string

    Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • timeout string

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • acknowledged boolean Required

      For a successful response, this value is always true. On failure, an exception is returned instead.
PUT /_data_stream/{name} 
curl \
 --request PUT 'http://api.example.com/_data_stream/{name}' \
 --header "Authorization: $API_KEY"

Get data stream lifecycle stats Added in 8.12.0

GET /_lifecycle/stats
Api key auth Basic auth Bearer auth

Get statistics about the data streams that are managed by a data stream lifecycle.

Responses

GET /_lifecycle/stats 
curl \
 --request GET 'http://api.example.com/_lifecycle/stats' \
 --header "Authorization: $API_KEY"
Response examples (200)
A successful response for `GET _lifecycle/stats?human&pretty` 
{
  "last_run_duration_in_millis": 2,
  "last_run_duration": "2ms",
  "time_between_starts_in_millis": 9998,
  "time_between_starts": "9.99s",
  "data_streams_count": 2,
  "data_streams": [
    {
      "name": "my-data-stream",
      "backing_indices_in_total": 2,
      "backing_indices_in_error": 0
    },
    {
      "name": "my-other-stream",
      "backing_indices_in_total": 2,
      "backing_indices_in_error": 1
    }
  ]
}

Document

Learn more about reading and writing documents

Create an enrich policy Added in 7.5.0

PUT /_enrich/policy/{name}
Api key auth Basic auth Bearer auth

Creates an enrich policy.

Path parameters

  • name string Required

    Name of the enrich policy to create or update.

Query parameters

  • master_timeout string

    Period to wait for a connection to the master node.

    Values are -1 or 0.

application/json

Body Required

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • acknowledged boolean Required

      For a successful response, this value is always true. On failure, an exception is returned instead.
PUT /_enrich/policy/{name} 
curl \
 --request PUT 'http://api.example.com/_enrich/policy/{name}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '{"additionalProperty1":{"enrich_fields":"string","indices":"string","match_field":"string","query":{},"name":"string","elasticsearch_version":"string"},"additionalProperty2":{"enrich_fields":"string","indices":"string","match_field":"string","query":{},"name":"string","elasticsearch_version":"string"}}'

Graph explore

The graph explore API enables you to extract and summarize information about the documents and terms in an Elasticsearch data stream or index.

Get started with Graph

Delete indices

DELETE /{index}
Api key auth Basic auth Bearer auth

Deleting an index deletes its documents, shards, and metadata. It does not delete related Kibana components, such as data views, visualizations, or dashboards.

You cannot delete the current write index of a data stream. To delete the index, you must roll over the data stream so a new write index is created. You can then use the delete index API to delete the previous write index.

Path parameters

  • index string | array[string] Required

    Comma-separated list of indices to delete. You cannot specify index aliases. By default, this parameter does not support wildcards (*) or _all. To use wildcards or _all, set the action.destructive_requires_name cluster setting to false.

Query parameters

  • allow_no_indices boolean

    If false, the request returns an error if any wildcard expression, index alias, or _all value targets only missing or closed indices. This behavior applies even if the request targets other open indices.

  • expand_wildcards string | array[string]

    Type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. Supports comma-separated values, such as open,hidden. Valid values are: all, open, closed, hidden, none.

    Supported values include:

    • all: Match any data stream or index, including hidden ones.
    • open: Match open, non-hidden indices. Also matches any non-hidden data stream.
    • closed: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.
    • hidden: Match hidden data streams and hidden indices. Must be combined with open, closed, or both.
    • none: Wildcard expressions are not accepted.

    Values are all, open, closed, hidden, or none.

  • ignore_unavailable boolean

    If false, the request returns an error if it targets a missing or closed index.

  • master_timeout string

    Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • timeout string

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
DELETE /{index} 
curl \
 --request DELETE 'http://api.example.com/{index}' \
 --header "Authorization: $API_KEY"

Get lifecycle policies Added in 6.6.0

GET /_ilm/policy/{policy}
Api key auth Basic auth Bearer auth

Path parameters

  • policy string Required

    Identifier for the policy.

Query parameters

  • master_timeout string

    Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • timeout string

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

Responses

GET /_ilm/policy/{policy} 
curl \
 --request GET 'http://api.example.com/_ilm/policy/{policy}' \
 --header "Authorization: $API_KEY"
Response examples (200)
A successful response when retrieving a lifecycle policy. 
{
  "my_policy": {
    "version": 1,
    "modified_date": 82392349,
    "policy": {
      "phases": {
        "warm": {
          "min_age": "10d",
          "actions": {
            "forcemerge": {
              "max_num_segments": 1
            }
          }
        },
        "delete": {
          "min_age": "30d",
          "actions": {
            "delete": {
              "delete_searchable_snapshot": true
            }
          }
        }
      }
    },
    "in_use_by" : {
      "indices" : [],
      "data_streams" : [],
      "composable_templates" : []
    }
  }
}

Create or update a lifecycle policy Added in 6.6.0

PUT /_ilm/policy/{policy}
Api key auth Basic auth Bearer auth

If the specified policy exists, it is replaced and the policy version is incremented.

NOTE: Only the latest version of the policy is stored, you cannot revert to previous versions.

External documentation

Path parameters

  • policy string Required

    Identifier for the policy.

Query parameters

  • master_timeout string

    Period to wait for a connection to the master node. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

  • timeout string

    Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.

    Values are -1 or 0.

application/json

Body

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • acknowledged boolean Required

      For a successful response, this value is always true. On failure, an exception is returned instead.
PUT /_ilm/policy/{policy} 
curl \
 --request PUT 'http://api.example.com/_ilm/policy/{policy}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"policy\": {\n    \"_meta\": {\n      \"description\": \"used for nginx log\",\n      \"project\": {\n        \"name\": \"myProject\",\n        \"department\": \"myDepartment\"\n      }\n    },\n    \"phases\": {\n      \"warm\": {\n        \"min_age\": \"10d\",\n        \"actions\": {\n          \"forcemerge\": {\n            \"max_num_segments\": 1\n          }\n        }\n      },\n      \"delete\": {\n        \"min_age\": \"30d\",\n        \"actions\": {\n          \"delete\": {}\n        }\n      }\n    }\n  }\n}"'
Request example
Run `PUT _ilm/policy/my_policy` to create a new policy with arbitrary metadata. 
{
  "policy": {
    "_meta": {
      "description": "used for nginx log",
      "project": {
        "name": "myProject",
        "department": "myDepartment"
      }
    },
    "phases": {
      "warm": {
        "min_age": "10d",
        "actions": {
          "forcemerge": {
            "max_num_segments": 1
          }
        }
      },
      "delete": {
        "min_age": "30d",
        "actions": {
          "delete": {}
        }
      }
    }
  }
}
Response examples (200)
A successful response when creating a new lifecycle policy. 
{
  "acknowledged": true
}

Inference

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 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.

Perform chat completion inference Added in 8.18.0

POST /_inference/chat_completion/{inference_id}/_stream
Api key auth Basic auth Bearer auth

The chat completion inference API enables real-time responses for chat completion tasks by delivering answers incrementally, reducing response times during computation. It only works with the chat_completion task type for openai and elastic inference services.

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.

NOTE: The chat_completion task type is only available within the _stream API and only supports streaming. 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.

Path parameters

Query parameters

  • timeout string

    Specifies the amount of time to wait for the inference request to complete.

    Values are -1 or 0.

application/json

Body Required

  • messages array[object] Required

    A list of objects representing the conversation. Requests should generally only add new messages from the user (role user). The other message roles (assistant, system, or tool) should generally only be copied from the response to a previous completion request, such that the messages array is built up throughout a conversation.

    Hide messages attributes Show messages attributes object
  • model string

    The ID of the model to use.

  • max_completion_tokens number

    The upper bound limit for the number of tokens that can be generated for a completion request.

  • stop array[string]

    A sequence of strings to control when the model should stop generating additional tokens.

  • temperature number

    The sampling temperature to use.

  • tool_choice string | object

    One of:
    CompletionToolType string CompletionToolChoice object
  • tools array[object]

    A list of tools that the model can call.

    Hide tools attributes Show tools attributes object
    • type string Required

      The type of tool.

    • function object Required
      Hide function attributes Show function attributes object
      • description string

        A description of what the function does. This is used by the model to choose when and how to call the function.

      • name string Required

        The name of the function.

      • parameters object

        The parameters the functional accepts. This should be formatted as a JSON object.

      • strict boolean

        Whether to enable schema adherence when generating the function call.

  • top_p number

    Nucleus sampling, an alternative to sampling with temperature.

Responses

POST /_inference/chat_completion/{inference_id}/_stream 
curl \
 --request POST 'http://api.example.com/_inference/chat_completion/{inference_id}/_stream' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n  \"model\": \"gpt-4o\",\n  \"messages\": [\n      {\n          \"role\": \"user\",\n          \"content\": \"What is Elastic?\"\n      }\n  ]\n}"'
Request examples
Run `POST _inference/chat_completion/openai-completion/_stream` to perform a chat completion on the example question with streaming. 
{
  "model": "gpt-4o",
  "messages": [
      {
          "role": "user",
          "content": "What is Elastic?"
      }
  ]
}
Run `POST POST _inference/chat_completion/openai-completion/_stream` to perform a chat completion using an Assistant message with `tool_calls`. 
{
  "messages": [
      {
          "role": "assistant",
          "content": "Let's find out what the weather is",
          "tool_calls": [ 
              {
                  "id": "call_KcAjWtAww20AihPHphUh46Gd",
                  "type": "function",
                  "function": {
                      "name": "get_current_weather",
                      "arguments": "{\"location\":\"Boston, MA\"}"
                  }
              }
          ]
      },
      { 
          "role": "tool",
          "content": "The weather is cold",
          "tool_call_id": "call_KcAjWtAww20AihPHphUh46Gd"
      }
  ]
}
Run `POST POST _inference/chat_completion/openai-completion/_stream` to perform a chat completion using a User message with `tools` and `tool_choice`. 
{
  "messages": [
      {
          "role": "user",
          "content": [
              {
                  "type": "text",
                  "text": "What's the price of a scarf?"
              }
          ]
      }
  ],
  "tools": [
      {
          "type": "function",
          "function": {
              "name": "get_current_price",
              "description": "Get the current price of a item",
              "parameters": {
                  "type": "object",
                  "properties": {
                      "item": {
                          "id": "123"
                      }
                  }
              }
          }
      }
  ],
  "tool_choice": {
      "type": "function",
      "function": {
          "name": "get_current_price"
      }
  }
}
Response examples (200)
A successful response when performing a chat completion task using a User message with `tools` and `tool_choice`. 
event: message
data: {"chat_completion":{"id":"chatcmpl-Ae0TWsy2VPnSfBbv5UztnSdYUMFP3","choices":[{"delta":{"content":"","role":"assistant"},"index":0}],"model":"gpt-4o-2024-08-06","object":"chat.completion.chunk"}}

event: message
data: {"chat_completion":{"id":"chatcmpl-Ae0TWsy2VPnSfBbv5UztnSdYUMFP3","choices":[{"delta":{"content":Elastic"},"index":0}],"model":"gpt-4o-2024-08-06","object":"chat.completion.chunk"}}

event: message
data: {"chat_completion":{"id":"chatcmpl-Ae0TWsy2VPnSfBbv5UztnSdYUMFP3","choices":[{"delta":{"content":" is"},"index":0}],"model":"gpt-4o-2024-08-06","object":"chat.completion.chunk"}}

(...)

event: message
data: {"chat_completion":{"id":"chatcmpl-Ae0TWsy2VPnSfBbv5UztnSdYUMFP3","choices":[],"model":"gpt-4o-2024-08-06","object":"chat.completion.chunk","usage":{"completion_tokens":28,"prompt_tokens":16,"total_tokens":44}}} 

event: message
data: [DONE]

Create an Elasticsearch inference endpoint Added in 8.13.0

PUT /_inference/{task_type}/{elasticsearch_inference_id}
Api key auth Basic auth Bearer auth

Create an inference endpoint to perform an inference task with the elasticsearch service.


Your Elasticsearch deployment contains preconfigured ELSER and E5 inference endpoints, you only need to create the enpoints using the API if you want to customize the settings.

If you use the ELSER or the E5 model through the elasticsearch service, the API request will automatically download and deploy the model if it isn't downloaded yet.


You might see a 502 bad gateway error in the response when using the Kibana Console. This error usually just reflects a timeout, while the model downloads in the background. You can check the download progress in the Machine Learning UI. If using the Python client, you can set the timeout parameter to a higher value.

After creating the endpoint, wait for the model deployment to complete before using it. To verify the deployment status, use the get trained model statistics API. Look for "state": "fully_allocated" in the response and ensure that the "allocation_count" matches the "target_allocation_count". Avoid creating multiple endpoints for the same model unless required, as each endpoint consumes significant resources.

Path parameters

  • task_type string Required

    The type of the inference task that the model will perform.

    Values are rerank, sparse_embedding, or text_embedding.

  • elasticsearch_inference_id string Required

    The unique identifier of the inference endpoint. The must not match the model_id.

application/json

Body

  • chunking_settings object
    Hide chunking_settings attributes Show chunking_settings attributes object
    • max_chunk_size number

      The maximum size of a chunk in words. This value cannot be higher than 300 or lower than 20 (for sentence strategy) or 10 (for word strategy).

    • overlap number

      The number of overlapping words for chunks. It is applicable only to a word chunking strategy. This value cannot be higher than half the max_chunk_size value.

    • sentence_overlap number

      The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.

    • strategy string

      The chunking strategy: sentence or word.

  • service string Required

    Value is elasticsearch.

  • service_settings object Required
    Hide service_settings attributes Show service_settings attributes object
    • adaptive_allocations object
      Hide adaptive_allocations attributes Show adaptive_allocations attributes object
      • enabled boolean

        Turn on adaptive_allocations.

      • max_number_of_allocations number

        The maximum number of allocations to scale to. If set, it must be greater than or equal to min_number_of_allocations.

      • min_number_of_allocations number

        The minimum number of allocations to scale to. If set, it must be greater than or equal to 0. If not defined, the deployment scales to 0.

    • deployment_id string

      The deployment identifier for a trained model deployment. When deployment_id is used the model_id is optional.

    • model_id string Required

      The name of the model to use for the inference task. It can be the ID of a built-in model (for example, .multilingual-e5-small for E5) or a text embedding model that was uploaded by using the Eland client.

      External documentation
    • num_allocations number

      The total number of allocations that are assigned to the model across machine learning nodes. Increasing this value generally increases the throughput. If adaptive allocations are enabled, do not set this value because it's automatically set.

    • num_threads number Required

      The number of threads used by each model allocation during inference. This setting generally increases the speed per inference request. The inference process is a compute-bound process; threads_per_allocations must not exceed the number of available allocated processors per node. The value must be a power of 2. The maximum value is 32.

  • task_settings object
    Hide task_settings attribute Show task_settings attribute object
    • return_documents boolean

      For a rerank task, return the document instead of only the index.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • chunking_settings object
      Hide chunking_settings attributes Show chunking_settings attributes object
      • max_chunk_size number

        The maximum size of a chunk in words. This value cannot be higher than 300 or lower than 20 (for sentence strategy) or 10 (for word strategy).

      • overlap number

        The number of overlapping words for chunks. It is applicable only to a word chunking strategy. This value cannot be higher than half the max_chunk_size value.

      • sentence_overlap number

        The number of overlapping sentences for chunks. It is applicable only for a sentence chunking strategy. It can be either 1 or 0.

      • strategy string

        The chunking strategy: sentence or word.

    • service string Required

      The service type

    • service_settings object Required
    • task_settings object
    • inference_id string Required

      The inference Id

    • task_type string Required

      Values are sparse_embedding, text_embedding, rerank, completion, or chat_completion.
PUT /_inference/{task_type}/{elasticsearch_inference_id} 
curl \
 --request PUT 'http://api.example.com/_inference/{task_type}/{elasticsearch_inference_id}' \
 --header "Authorization: $API_KEY" \
 --header "Content-Type: application/json" \
 --data '"{\n    \"service\": \"elasticsearch\",\n    \"service_settings\": {\n        \"adaptive_allocations\": { \n        \"enabled\": true,\n        \"min_number_of_allocations\": 1,\n        \"max_number_of_allocations\": 4\n        },\n        \"num_threads\": 1,\n        \"model_id\": \".elser_model_2\" \n    }\n}"'
Request examples
Run `PUT _inference/sparse_embedding/my-elser-model` to create an inference endpoint that performs a `sparse_embedding` task. The `model_id` must be the ID of one of the built-in ELSER models. The API will automatically download the ELSER model if it isn't already downloaded and then deploy the model. 
{
    "service": "elasticsearch",
    "service_settings": {
        "adaptive_allocations": { 
        "enabled": true,
        "min_number_of_allocations": 1,
        "max_number_of_allocations": 4
        },
        "num_threads": 1,
        "model_id": ".elser_model_2" 
    }
}
Run `PUT _inference/rerank/my-elastic-rerank` to create an inference endpoint that performs a rerank task using the built-in Elastic Rerank cross-encoder model. The `model_id` must be `.rerank-v1`, which is the ID of the built-in Elastic Rerank model. The API will automatically download the Elastic Rerank model if it isn't already downloaded and then deploy the model. Once deployed, the model can be used for semantic re-ranking with a `text_similarity_reranker` retriever. 
{
    "service": "elasticsearch",
    "service_settings": {
        "model_id": ".rerank-v1", 
        "num_threads": 1,
        "adaptive_allocations": { 
        "enabled": true,
        "min_number_of_allocations": 1,
        "max_number_of_allocations": 4
        }
    }
}
Run `PUT _inference/text_embedding/my-e5-model` to create an inference endpoint that performs a `text_embedding` task. The `model_id` must be the ID of one of the built-in E5 models. The API will automatically download the E5 model if it isn't already downloaded and then deploy the model. 
{
    "service": "elasticsearch",
    "service_settings": {
        "num_allocations": 1,
        "num_threads": 1,
        "model_id": ".multilingual-e5-small" 
    }
}
Run `PUT _inference/text_embedding/my-msmarco-minilm-model` to create an inference endpoint that performs a `text_embedding` task with a model that was uploaded by Eland. 
{
    "service": "elasticsearch",
    "service_settings": {
        "num_allocations": 1,
        "num_threads": 1,
        "model_id": "msmarco-MiniLM-L12-cos-v5" 
    }
}
Run `PUT _inference/text_embedding/my-e5-model` to create an inference endpoint that performs a `text_embedding` task and to configure adaptive allocations. The API request will automatically download the E5 model if it isn't already downloaded and then deploy the model. 
{
    "service": "elasticsearch",
    "service_settings": {
        "adaptive_allocations": {
        "enabled": true,
        "min_number_of_allocations": 3,
        "max_number_of_allocations": 10
        },
        "num_threads": 1,
        "model_id": ".multilingual-e5-small"
    }
}
Run `PUT _inference/sparse_embedding/use_existing_deployment` to use an already existing model deployment when creating an inference endpoint. 
{
    "service": "elasticsearch",
    "service_settings": {
        "deployment_id": ".elser_model_2"
    }
}
Response examples (200)
A successful response from `PUT _inference/sparse_embedding/use_existing_deployment`. It contains the model ID and the threads and allocations settings from the model deployment. 
{
  "inference_id": "use_existing_deployment",
  "task_type": "sparse_embedding",
  "service": "elasticsearch",
  "service_settings": {
    "num_allocations": 2,
    "num_threads": 1,
    "model_id": ".elser_model_2",
    "deployment_id": ".elser_model_2"
  },
  "chunking_settings": {
    "strategy": "sentence",
    "max_chunk_size": 250,
    "sentence_overlap": 1
  }
}