Create embeddings
curl --request POST \
--url https://api.aisa.one/v1/embeddings \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "jina-embeddings-v3",
"input": "A fast, OpenAI-compatible embeddings endpoint."
}
'import requests
url = "https://api.aisa.one/v1/embeddings"
payload = {
"model": "jina-embeddings-v3",
"input": "A fast, OpenAI-compatible embeddings endpoint."
}
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({
model: 'jina-embeddings-v3',
input: 'A fast, OpenAI-compatible embeddings endpoint.'
})
};
fetch('https://api.aisa.one/v1/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.aisa.one/v1/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([
'model' => 'jina-embeddings-v3',
'input' => 'A fast, OpenAI-compatible embeddings endpoint.'
]),
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.aisa.one/v1/embeddings"
payload := strings.NewReader("{\n \"model\": \"jina-embeddings-v3\",\n \"input\": \"A fast, OpenAI-compatible embeddings endpoint.\"\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.aisa.one/v1/embeddings")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"jina-embeddings-v3\",\n \"input\": \"A fast, OpenAI-compatible embeddings endpoint.\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/v1/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 \"model\": \"jina-embeddings-v3\",\n \"input\": \"A fast, OpenAI-compatible embeddings endpoint.\"\n}"
response = http.request(request)
puts response.read_body{
"object": "list",
"data": [
{
"object": "embedding",
"index": 0,
"embedding": [
0.0123,
-0.0456,
0.0789
]
}
],
"model": "jina-embeddings-v3",
"usage": {
"total_tokens": 9
}
}Embeddings & Rerank
Create Embeddings
Generate embedding vectors from text using Jina embeddings, served via the OpenAI-compatible AIsa relay.
POST
https://api.aisa.one/v1
/
embeddings
Create embeddings
curl --request POST \
--url https://api.aisa.one/v1/embeddings \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "jina-embeddings-v3",
"input": "A fast, OpenAI-compatible embeddings endpoint."
}
'import requests
url = "https://api.aisa.one/v1/embeddings"
payload = {
"model": "jina-embeddings-v3",
"input": "A fast, OpenAI-compatible embeddings endpoint."
}
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({
model: 'jina-embeddings-v3',
input: 'A fast, OpenAI-compatible embeddings endpoint.'
})
};
fetch('https://api.aisa.one/v1/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.aisa.one/v1/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([
'model' => 'jina-embeddings-v3',
'input' => 'A fast, OpenAI-compatible embeddings endpoint.'
]),
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.aisa.one/v1/embeddings"
payload := strings.NewReader("{\n \"model\": \"jina-embeddings-v3\",\n \"input\": \"A fast, OpenAI-compatible embeddings endpoint.\"\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.aisa.one/v1/embeddings")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"jina-embeddings-v3\",\n \"input\": \"A fast, OpenAI-compatible embeddings endpoint.\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/v1/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 \"model\": \"jina-embeddings-v3\",\n \"input\": \"A fast, OpenAI-compatible embeddings endpoint.\"\n}"
response = http.request(request)
puts response.read_body{
"object": "list",
"data": [
{
"object": "embedding",
"index": 0,
"embedding": [
0.0123,
-0.0456,
0.0789
]
}
],
"model": "jina-embeddings-v3",
"usage": {
"total_tokens": 9
}
}Generate embedding vectors for one or more input strings. Pass a non-empty
input string, or an array of strings for batch embedding. The request and response are OpenAI-compatible, so the OpenAI SDK works unchanged by pointing base_url at the AIsa relay.
Available models (both 1024-dim output):
jina-embeddings-v3jina-embeddings-v5-text-small
/v1/embeddings — OpenAI-compatible. Billing is token-based at $0.050 per 1M tokens; the usage.total_tokens field reports the tokens billed for each request.
curl https://api.aisa.one/v1/embeddings \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "jina-embeddings-v3",
"input": "A fast, OpenAI-compatible embeddings endpoint."
}'
curl https://api.aisa.one/v1/embeddings \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "jina-embeddings-v5-text-small",
"input": "A fast, OpenAI-compatible embeddings endpoint."
}'
from openai import OpenAI
client = OpenAI(base_url="https://api.aisa.one/v1", api_key="sk-aisa-...")
resp = client.embeddings.create(
model="jina-embeddings-v5-text-small", # or "jina-embeddings-v3"
input="A fast, OpenAI-compatible embeddings endpoint.",
)
print(resp.data[0].embedding) # 1024-dim vector
Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
application/json
Embedding model name. Available: jina-embeddings-v3 or jina-embeddings-v5-text-small (both 1024-dim).
Available options:
jina-embeddings-v3, jina-embeddings-v5-text-small Example:
"jina-embeddings-v3"
A non-empty string, or an array of non-empty strings, to embed.
Example:
"A fast, OpenAI-compatible embeddings endpoint."