Perform reranking inference on the service Generally available; Added in 8.11.0

POST /_inference/rerank/{inference_id}
Api key auth Basic auth Bearer auth

Required authorization

  • Cluster privileges: monitor_inference

Path parameters

  • inference_id string Required

    The unique identifier for the inference endpoint.

Query parameters

application/json

Body

  • query string Required

    Query input.

  • input string | array[string] Required

    The text on which you want to perform the inference task. It can be a single string or an array.


    Inference endpoints for the completion task type currently only support a single string as input.

    One of:
    string-1 string array-2 array[string]
  • 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
      • 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"
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"
    }
  ]
}