curl --request POST \
--url https://api.edenai.run/v3/embeddings \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"input": "<string>",
"model": "<string>",
"encoding_format": "float",
"dimensions": 1,
"user": "<string>",
"metadata": {},
"extra_headers": {}
}
'import requests
url = "https://api.edenai.run/v3/embeddings"
payload = {
"input": "<string>",
"model": "<string>",
"encoding_format": "float",
"dimensions": 1,
"user": "<string>",
"metadata": {},
"extra_headers": {}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
input: '<string>',
model: '<string>',
encoding_format: 'float',
dimensions: 1,
user: '<string>',
metadata: {},
extra_headers: {}
})
};
fetch('https://api.edenai.run/v3/embeddings', 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.edenai.run/v3/embeddings",
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([
'input' => '<string>',
'model' => '<string>',
'encoding_format' => 'float',
'dimensions' => 1,
'user' => '<string>',
'metadata' => [
],
'extra_headers' => [
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($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.edenai.run/v3/embeddings"
payload := strings.NewReader("{\n \"input\": \"<string>\",\n \"model\": \"<string>\",\n \"encoding_format\": \"float\",\n \"dimensions\": 1,\n \"user\": \"<string>\",\n \"metadata\": {},\n \"extra_headers\": {}\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
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.edenai.run/v3/embeddings")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"input\": \"<string>\",\n \"model\": \"<string>\",\n \"encoding_format\": \"float\",\n \"dimensions\": 1,\n \"user\": \"<string>\",\n \"metadata\": {},\n \"extra_headers\": {}\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.edenai.run/v3/embeddings")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"input\": \"<string>\",\n \"model\": \"<string>\",\n \"encoding_format\": \"float\",\n \"dimensions\": 1,\n \"user\": \"<string>\",\n \"metadata\": {},\n \"extra_headers\": {}\n}"
response = http.request(request)
puts response.read_body{
"data": [
{
"embedding": [
123
],
"index": 123,
"object": "embedding"
}
],
"model": "<string>",
"object": "list",
"usage": {
"prompt_tokens": 123,
"total_tokens": 123
},
"cost": 123,
"provider": "<string>"
}{
"detail": [
{
"loc": [
"<string>"
],
"msg": "<string>",
"type": "<string>"
}
]
}Create Embeddings
OpenAI-compatible embeddings endpoint.
curl --request POST \
--url https://api.edenai.run/v3/embeddings \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"input": "<string>",
"model": "<string>",
"encoding_format": "float",
"dimensions": 1,
"user": "<string>",
"metadata": {},
"extra_headers": {}
}
'import requests
url = "https://api.edenai.run/v3/embeddings"
payload = {
"input": "<string>",
"model": "<string>",
"encoding_format": "float",
"dimensions": 1,
"user": "<string>",
"metadata": {},
"extra_headers": {}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
input: '<string>',
model: '<string>',
encoding_format: 'float',
dimensions: 1,
user: '<string>',
metadata: {},
extra_headers: {}
})
};
fetch('https://api.edenai.run/v3/embeddings', 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.edenai.run/v3/embeddings",
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([
'input' => '<string>',
'model' => '<string>',
'encoding_format' => 'float',
'dimensions' => 1,
'user' => '<string>',
'metadata' => [
],
'extra_headers' => [
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($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.edenai.run/v3/embeddings"
payload := strings.NewReader("{\n \"input\": \"<string>\",\n \"model\": \"<string>\",\n \"encoding_format\": \"float\",\n \"dimensions\": 1,\n \"user\": \"<string>\",\n \"metadata\": {},\n \"extra_headers\": {}\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
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.edenai.run/v3/embeddings")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"input\": \"<string>\",\n \"model\": \"<string>\",\n \"encoding_format\": \"float\",\n \"dimensions\": 1,\n \"user\": \"<string>\",\n \"metadata\": {},\n \"extra_headers\": {}\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.edenai.run/v3/embeddings")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"input\": \"<string>\",\n \"model\": \"<string>\",\n \"encoding_format\": \"float\",\n \"dimensions\": 1,\n \"user\": \"<string>\",\n \"metadata\": {},\n \"extra_headers\": {}\n}"
response = http.request(request)
puts response.read_body{
"data": [
{
"embedding": [
123
],
"index": 123,
"object": "embedding"
}
],
"model": "<string>",
"object": "list",
"usage": {
"prompt_tokens": 123,
"total_tokens": 123
},
"cost": 123,
"provider": "<string>"
}{
"detail": [
{
"loc": [
"<string>"
],
"msg": "<string>",
"type": "<string>"
}
]
}Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
OpenAI-compatible POST /v1/embeddings request body, plus minimal Eden extensions.
Unknown top-level fields are forwarded to the underlying provider.
Input to embed: string, list of strings, pre-tokenized list of ints, or pre-tokenized batch (list of int lists). Max 2048 items for OpenAI.
Model identifier in 'provider/model' format, e.g. 'openai/text-embedding-3-small'.
Output encoding: 'float' (default) or 'base64'.
float, base64 Reduce output vector size. 3-series models only.
x > 0End-user identifier for abuse tracking.
Arbitrary metadata attached to the request.
Additional HTTP headers forwarded to the provider API.
Show child attributes
Show child attributes
Response
Successful Response
OpenAI-compatible embeddings response + Eden cost and provider fields.
EmbeddingsDataClass (from edenai-apis) already widens
data[].embedding to list[float] | str so the base64 wire format
validates here too.
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