The API accepts 3 different authentication methods:
Elasticsearch APIs support key-based authentication. You must create an API key and use the encoded value in the request header. For example:
curl -X GET "${ES_URL}/_cat/indices?v=true" \
-H "Authorization: ApiKey ${API_KEY}"
To get API keys, use the /_security/api_key APIs.
Elasticsearch APIs support the use of bearer tokens in the Authorization HTTP header to authenticate with the API.
For examples, refer to Token-based authentication services
Asynchronously run an ES|QL (Elasticsearch query language) query, monitor its progress, and retrieve results when they become available.
The API accepts the same parameters and request body as the synchronous query API, along with additional async related properties.
readThe character to use between values within a CSV row. It is valid only for the CSV format.
Indicates whether columns that are entirely null will be removed from the columns and values portion of the results.
If true, the response will include an extra section under the name all_columns which has the name of all the columns.
A short version of the Accept header, for example json or yaml.
Values are csv, json, tsv, txt, yaml, cbor, smile, or arrow.
By default, ES|QL returns results as rows. For example, FROM returns each individual document as one row. For the JSON, YAML, CBOR and smile formats, ES|QL can return the results in a columnar fashion where one row represents all the values of a certain column in the results.
An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
To avoid any attempts of hacking or code injection, extract the values in a separate list of parameters. Use question mark placeholders (?) in the query string for each of the parameters.
A field value.
A field value.
If provided and true the response will include an extra profile object
with information on how the query was executed. This information is for human debugging
and its format can change at any time but it can give some insight into the performance
of each part of the query.
The ES|QL query API accepts an ES|QL query string in the query parameter, runs it, and returns the results.
Tables to use with the LOOKUP operation. The top level key is the table name and the next level key is the column name.
When set to true and performing a cross-cluster query, the response will include an extra _clusters
object with information about the clusters that participated in the search along with info such as shards
count.
A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and
d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.
A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and
d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.
Indicates whether the query and its results are stored in the cluster.
If false, the query and its results are stored in the cluster only if the request does not complete during the period set by the wait_for_completion_timeout parameter.
curl \
--request POST 'http://api.example.com/_query/async' \
--header "Authorization: $API_KEY" \
--header "Content-Type: application/json" \
--data '"{\n \"query\": \"\"\"\n FROM library,remote-*:library\n | EVAL year = DATE_TRUNC(1 YEARS, release_date)\n | STATS MAX(page_count) BY year\n | SORT year\n | LIMIT 5\n \"\"\",\n \"wait_for_completion_timeout\": \"2s\",\n \"include_ccs_metadata\": true\n}"'{
"query": """
FROM library,remote-*:library
| EVAL year = DATE_TRUNC(1 YEARS, release_date)
| STATS MAX(page_count) BY year
| SORT year
| LIMIT 5
""",
"wait_for_completion_timeout": "2s",
"include_ccs_metadata": true
}This API interrupts the query execution and returns the results so far. If the Elasticsearch security features are enabled, only the user who first submitted the ES|QL query can stop it.
The unique identifier of the query.
A query ID is provided in the ES|QL async query API response for a query that does not complete in the designated time.
A query ID is also provided when the request was submitted with the keep_on_completion parameter set to true.
curl \
--request POST 'http://api.example.com/_query/async/{id}/stop' \
--header "Authorization: $API_KEY"Comma-separated list of component template names used to limit the request.
Wildcard (*) expressions are supported.
If true, returns settings in flat format.
Return all default configurations for the component template (default: false)
If true, the request retrieves information from the local node only.
If false, information is retrieved from the master node.
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.
curl \
--request GET 'http://api.example.com/_component_template/{name}' \
--header "Authorization: $API_KEY"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.
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, elastic and googlevertexai inference services.
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.
Specifies the amount of time to wait for the inference request to complete.
Values are -1 or 0.
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.
An object representing part of the conversation.
The ID of the model to use.
The upper bound limit for the number of tokens that can be generated for a completion request.
A sequence of strings to control when the model should stop generating additional tokens.
The sampling temperature to use.
A list of tools that the model can call. Example:
{
"tools": [
{
"type": "function",
"function": {
"name": "get_price_of_item",
"description": "Get the current price of an item",
"parameters": {
"type": "object",
"properties": {
"item": {
"id": "12345"
},
"unit": {
"type": "currency"
}
}
}
}
}
]
}
A list of tools that the model can call.
Nucleus sampling, an alternative to sampling with temperature.
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}"'{
"model": "gpt-4o",
"messages": [
{
"role": "user",
"content": "What is Elastic?"
}
]
}{
"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"
}
]
}{
"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"
}
}
}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]Specifies what to do when the request:
_all string or no identifiers and there are no matches.The default value returns an empty data_frame_analytics array when there
are no matches and the subset of results when there are partial matches.
If this parameter is false, the request returns a 404 status code when
there are no matches or only partial matches.
Skips the specified number of data frame analytics jobs.
Specifies the maximum number of data frame analytics jobs to obtain.
Defines whether the stats response should be verbose.
curl \
--request GET 'http://api.example.com/_ml/data_frame/analytics/_stats' \
--header "Authorization: $API_KEY"