Perform reranking inference on the service Generally available

POST /_inference/rerank/{inference_id}

Required authorization

  • Cluster privileges: monitor_inference

Path parameters

  • inference_id string Required

    The unique identifier for the inference endpoint.

Query parameters

application/json

Body Required

  • query string | object Required

    Query input. The query can be specified as a single string, or as an object. The object form additionally allows specifying non-text inputs, such as images.


    Only the elastic service currently supports non-text queries for the rerank task. For all other services, the query must be a string.

    string example:

    "query": "some query text"
    

    object example:

    "query": {
      "type": "image",
      "format": "base64",
      "value": "data:image/jpeg;base64,..."
    }
    
    One of:
  • input string | array[string] | object | array[object] Required

    The documents to rank. The input can be specified as a single string or an array of strings, or as an object or an array of objects. The object form additionally allows specifying non-text inputs, such as images.


    Only the elastic service currently supports non-text inputs for the rerank task. For all other services, the input must be a string or an array of strings.

    string example:

    "input": "some document text"
    

    string array example:

    "input": ["some document text", "some more document text"]
    

    object example:

    "input": {
      "type": "image",
      "format": "base64",
      "value": "data:image/jpeg;base64,..."
    }
    

    object array example:

    "input": [
      {
        "type": "text",
        "format": "text",
        "value": "some document text"
      },
      {
        "type": "image",
        "format": "base64",
        "value": "data:image/jpeg;base64,..."
      }
    ]
    
    One of:

    An array of text documents to rank.

    An array of input objects to rank. Each object can specify a non-text input, such as an image.

  • return_documents boolean

    Include the document text in the response.

  • top_n number

    Limit the response to the top N documents.

  • task_settings object

    Task settings for the individual inference request. These settings are specific to the task type you specified and override the task settings specified when initializing the service.

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • rerank array[object] Required

      The rerank result object representing a single ranked document id: the original index of the document in the request relevance_score: the relevance_score of the document relative to the query text: Optional, the text of the document, if requested

      Hide rerank attributes Show rerank attributes object

      The rerank result object representing a single ranked document id: the original index of the document in the request relevance_score: the relevance_score of the document relative to the query text: Optional, the text of the document, if requested

      • index number Required
      • relevance_score number Required
      • text string
POST /_inference/rerank/{inference_id}
POST _inference/rerank/cohere_rerank
{
  "input": ["luke", "like", "leia", "chewy","r2d2", "star", "wars"],
  "query": "star wars main character"
}
resp = client.inference.rerank(
    inference_id="cohere_rerank",
    input=[
        "luke",
        "like",
        "leia",
        "chewy",
        "r2d2",
        "star",
        "wars"
    ],
    query="star wars main character",
)
const response = await client.inference.rerank({
  inference_id: "cohere_rerank",
  input: ["luke", "like", "leia", "chewy", "r2d2", "star", "wars"],
  query: "star wars main character",
});
response = client.inference.rerank(
  inference_id: "cohere_rerank",
  body: {
    "input": [
      "luke",
      "like",
      "leia",
      "chewy",
      "r2d2",
      "star",
      "wars"
    ],
    "query": "star wars main character"
  }
)
$resp = $client->inference()->rerank([
    "inference_id" => "cohere_rerank",
    "body" => [
        "input" => array(
            "luke",
            "like",
            "leia",
            "chewy",
            "r2d2",
            "star",
            "wars",
        ),
        "query" => "star wars main character",
    ],
]);
curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"input":["luke","like","leia","chewy","r2d2","star","wars"],"query":"star wars main character"}' "$ELASTICSEARCH_URL/_inference/rerank/cohere_rerank"
client.inference().rerank(r -> r
    .inferenceId("cohere_rerank")
    .input(List.of("luke","like","leia","chewy","r2d2","star","wars"))
    .query("""
        star wars main character
        """)
);
Request examples
Run `POST _inference/rerank/cohere_rerank` to perform reranking on the example input.
{
  "input": ["luke", "like", "leia", "chewy","r2d2", "star", "wars"],
  "query": "star wars main character"
}
Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face
{
  "input": ["luke", "like", "leia", "chewy","r2d2", "star", "wars"],
  "query": "star wars main character",
  "return_documents": false,
  "top_n": 2
}
Run `POST _inference/rerank/bge-reranker-base-mkn` to perform reranking on the example input via Hugging Face
{
  "input": ["luke", "like", "leia", "chewy","r2d2", "star", "wars"],
  "query": "star wars main character",
  "return_documents": true,
  "top_n": 3
}
Response examples (200)
A successful response from `POST _inference/rerank/cohere_rerank`.
{
  "rerank": [
    {
      "index": "2",
      "relevance_score": "0.011597361",
      "text": "leia"
    },
    {
      "index": "0",
      "relevance_score": "0.006338922",
      "text": "luke"
    },
    {
      "index": "5",
      "relevance_score": "0.0016166499",
      "text": "star"
    },
    {
      "index": "4",
      "relevance_score": "0.0011695103",
      "text": "r2d2"
    },
    {
      "index": "1",
      "relevance_score": "5.614787E-4",
      "text": "like"
    },
    {
      "index": "6",
      "relevance_score": "3.7850367E-4",
      "text": "wars"
    },
    {
      "index": "3",
      "relevance_score": "1.2508839E-5",
      "text": "chewy"
    }
  ]
}
A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.
{
  "rerank": [
    {
      "index": 6,
      "relevance_score": 0.50955844
    },
    {
      "index": 5,
      "relevance_score": 0.084341794
    }
  ]
}
A successful response from `POST _inference/rerank/bge-reranker-base-mkn`.
{
  "rerank": [
    {
      "index": 6,
      "relevance_score": 0.50955844,
      "text": "wars"
    },
    {
      "index": 5,
      "relevance_score": 0.084341794,
      "text": "star"
    },
    {
      "index": 3,
      "relevance_score": 0.004520818,
      "text": "chewy"
    }
  ]
}