Get tokens from text analysis Generally available

POST /_analyze
Api key auth Basic auth Bearer auth

The analyze API performs analysis on a text string and returns the resulting tokens.

Generating excessive amount of tokens may cause a node to run out of memory. The index.analyze.max_token_count setting enables you to limit the number of tokens that can be produced. If more than this limit of tokens gets generated, an error occurs. The _analyze endpoint without a specified index will always use 10000 as its limit.

Required authorization

  • Index privileges: index
External documentation

Query parameters

  • index string

    Index used to derive the analyzer. If specified, the analyzer or field parameter overrides this value. If no index is specified or the index does not have a default analyzer, the analyze API uses the standard analyzer.

application/json

Body

  • analyzer string

    The name of the analyzer that should be applied to the provided text. This could be a built-in analyzer, or an analyzer that’s been configured in the index.

  • attributes array[string]

    Array of token attributes used to filter the output of the explain parameter.

  • char_filter array

    Array of character filters used to preprocess characters before the tokenizer.

    External documentation
  • explain boolean

    If true, the response includes token attributes and additional details.

  • field string

    Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

  • filter array

    Array of token filters used to apply after the tokenizer.

    External documentation
  • normalizer string

    Normalizer to use to convert text into a single token.

  • text string | array[string]

    One of:
    TextToAnalyze string TextToAnalyze array[string]

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • detail object
      Hide detail attributes Show detail attributes object
      • analyzer object
        Hide analyzer attributes Show analyzer attributes object
        • name string Required
        • tokens array[object] Required
          Hide tokens attributes Show tokens attributes object
          • bytes string Required
          • end_offset number Required
          • keyword boolean
          • position number Required
          • positionLength number Required
          • start_offset number Required
          • termFrequency number Required
          • token string Required
          • type string Required
      • charfilters array[object]
        Hide charfilters attributes Show charfilters attributes object
        • filtered_text array[string] Required
        • name string Required
      • custom_analyzer boolean Required
      • tokenfilters array[object]
        Hide tokenfilters attributes Show tokenfilters attributes object
        • name string Required
        • tokens array[object] Required
          Hide tokens attributes Show tokens attributes object
          • bytes string Required
          • end_offset number Required
          • keyword boolean
          • position number Required
          • positionLength number Required
          • start_offset number Required
          • termFrequency number Required
          • token string Required
          • type string Required
      • tokenizer object
        Hide tokenizer attributes Show tokenizer attributes object
        • name string Required
        • tokens array[object] Required
          Hide tokens attributes Show tokens attributes object
          • bytes string Required
          • end_offset number Required
          • keyword boolean
          • position number Required
          • positionLength number Required
          • start_offset number Required
          • termFrequency number Required
          • token string Required
          • type string Required
    • tokens array[object]
      Hide tokens attributes Show tokens attributes object
      • end_offset number Required
      • position number Required
      • positionLength number
      • start_offset number Required
      • token string Required
      • type string Required
POST /_analyze 
GET /_analyze
{
  "analyzer": "standard",
  "text": "this is a test"
}
resp = client.indices.analyze(
    analyzer="standard",
    text="this is a test",
)
const response = await client.indices.analyze({
  analyzer: "standard",
  text: "this is a test",
});
response = client.indices.analyze(
  body: {
    "analyzer": "standard",
    "text": "this is a test"
  }
)
$resp = $client->indices()->analyze([
    "body" => [
        "analyzer" => "standard",
        "text" => "this is a test",
    ],
]);
curl -X GET -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"analyzer":"standard","text":"this is a test"}' "$ELASTICSEARCH_URL/_analyze"
Request examples
You can apply any of the built-in analyzers to the text string without specifying an index. 
{
  "analyzer": "standard",
  "text": "this is a test"
}
If the text parameter is provided as array of strings, it is analyzed as a multi-value field. 
{
  "analyzer": "standard",
  "text": [
    "this is a test",
    "the second text"
  ]
}
You can test a custom transient analyzer built from tokenizers, token filters, and char filters. Token filters use the filter parameter. 
{
  "tokenizer": "keyword",
  "filter": [
    "lowercase"
  ],
  "char_filter": [
    "html_strip"
  ],
  "text": "this is a <b>test</b>"
}
Custom tokenizers, token filters, and character filters can be specified in the request body. 
{
  "tokenizer": "whitespace",
  "filter": [
    "lowercase",
    {
      "type": "stop",
      "stopwords": [
        "a",
        "is",
        "this"
      ]
    }
  ],
  "text": "this is a test"
}
Run `GET /analyze_sample/_analyze` to run an analysis on the text using the default index analyzer associated with the `analyze_sample` index. Alternatively, the analyzer can be derived based on a field mapping. 
{
  "field": "obj1.field1",
  "text": "this is a test"
}
Run `GET /analyze_sample/_analyze` and supply a normalizer for a keyword field if there is a normalizer associated with the specified index. 
{
  "normalizer": "my_normalizer",
  "text": "BaR"
}
If you want to get more advanced details, set `explain` to `true`. It will output all token attributes for each token. You can filter token attributes you want to output by setting the `attributes` option. NOTE: The format of the additional detail information is labelled as experimental in Lucene and it may change in the future. 
{
  "tokenizer": "standard",
  "filter": [
    "snowball"
  ],
  "text": "detailed output",
  "explain": true,
  "attributes": [
    "keyword"
  ]
}
Response examples (200)
A successful response for an analysis with `explain` set to `true`. 
{
  "detail": {
    "custom_analyzer": true,
    "charfilters": [],
    "tokenizer": {
      "name": "standard",
      "tokens": [
        {
          "token": "detailed",
          "start_offset": 0,
          "end_offset": 8,
          "type": "<ALPHANUM>",
          "position": 0
        },
        {
          "token": "output",
          "start_offset": 9,
          "end_offset": 15,
          "type": "<ALPHANUM>",
          "position": 1
        }
      ]
    },
    "tokenfilters": [
      {
        "name": "snowball",
        "tokens": [
          {
            "token": "detail",
            "start_offset": 0,
            "end_offset": 8,
            "type": "<ALPHANUM>",
            "position": 0,
            "keyword": false
          },
          {
            "token": "output",
            "start_offset": 9,
            "end_offset": 15,
            "type": "<ALPHANUM>",
            "position": 1,
            "keyword": false
          }
        ]
      }
    ]
  }
}