Search for embeddings

Search for embeddings using vector similarity search

POST /api/v1/embeddings/{indexName}/search

Search for embeddings

cURL

curl --request POST \
  --url https://api.example.com/api/v1/embeddings/{indexName}/search \
  --header 'Content-Type: application/json' \
  --header 'X-Eigen-API-Key: <api-key>' \
  --data '
{
  "queryVector": [
    123
  ],
  "k": 123
}
'

import requests

url = "https://api.example.com/api/v1/embeddings/{indexName}/search"

payload = {
    "queryVector": [123],
    "k": 123
}
headers = {
    "X-Eigen-API-Key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-Eigen-API-Key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({queryVector: [123], k: 123})
};

fetch('https://api.example.com/api/v1/embeddings/{indexName}/search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/api/v1/embeddings/{indexName}/search",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'queryVector' => [
        123
    ],
    'k' => 123
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-Eigen-API-Key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/api/v1/embeddings/{indexName}/search"

	payload := strings.NewReader("{\n  \"queryVector\": [\n    123\n  ],\n  \"k\": 123\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("X-Eigen-API-Key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/api/v1/embeddings/{indexName}/search")
  .header("X-Eigen-API-Key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"queryVector\": [\n    123\n  ],\n  \"k\": 123\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/embeddings/{indexName}/search")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["X-Eigen-API-Key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"queryVector\": [\n    123\n  ],\n  \"k\": 123\n}"

response = http.request(request)
puts response.read_body

200

{
  "status": 200,
  "message": "Similarity search successfully performed.",
  "data": {
    "nearest_neighbors": {
      "21": {
        "metadata": {
          "foo3": "bar4"
        },
        "rank": 2
      },
      "45": {
        "metadata": {
          "foo7": "bar8"
        },
        "rank": 4
      },
      "54": {
        "metadata": {
          "foo": "bar"
        },
        "rank": 0
      },
      "63": {
        "metadata": {
          "foo5": "bar6",
          "hello": "world"
        },
        "rank": 3
      },
      "98": {
        "metadata": {
          "foo1": "bar2",
          "bar": "baz"
        },
        "rank": 1
      }
    }
  }
}

{
  "status": 400,
  "message": "An error occured during the similarity search.",
  "error": {
    "code": "SIMILARITY_SEARCH_ERROR",
    "description": "detailed description of the error..."
  }
}

Authorizations

X-Eigen-API-Key · string · header · required

Path Parameters

indexName · string · required

Name of the index

Body

application/json

queryVector · number<float>[] · required

ID of the query vector

k · number<int> · required

Number of retrieved embedding desired.

Response

200

application/json

The k-nearest embeddings returned in an array along with their rank (0 is nearest).

status · integer · required

Status code of the response

message · string · required

Message giving basic information on the response

data · object

Important data to be given to the caller

error · object

An error that has occured

Show child attributes