Create a Vector Store
curl --request POST \
--url https://app.luly.ai/api/vectors \
--header 'Content-Type: application/json' \
--header 'authorization: <authorization>' \
--data '
{
"name": "<string>",
"description": "<string>",
"text": "<string>"
}
'import requests
url = "https://app.luly.ai/api/vectors"
payload = {
"name": "<string>",
"description": "<string>",
"text": "<string>"
}
headers = {
"authorization": "<authorization>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {authorization: '<authorization>', 'Content-Type': 'application/json'},
body: JSON.stringify({name: '<string>', description: '<string>', text: '<string>'})
};
fetch('https://app.luly.ai/api/vectors', 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://app.luly.ai/api/vectors",
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([
'name' => '<string>',
'description' => '<string>',
'text' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"authorization: <authorization>"
],
]);
$response = curl_exec($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://app.luly.ai/api/vectors"
payload := strings.NewReader("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"text\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("authorization", "<authorization>")
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://app.luly.ai/api/vectors")
.header("authorization", "<authorization>")
.header("Content-Type", "application/json")
.body("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"text\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://app.luly.ai/api/vectors")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["authorization"] = '<authorization>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"text\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"vector_id": "KB-55e64dae-1585-4632-ae97-c909c288c6bc"
}
Vector Stores
Create a Vector Store
Create a new vector store
POST
/
vectors
Create a Vector Store
curl --request POST \
--url https://app.luly.ai/api/vectors \
--header 'Content-Type: application/json' \
--header 'authorization: <authorization>' \
--data '
{
"name": "<string>",
"description": "<string>",
"text": "<string>"
}
'import requests
url = "https://app.luly.ai/api/vectors"
payload = {
"name": "<string>",
"description": "<string>",
"text": "<string>"
}
headers = {
"authorization": "<authorization>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {authorization: '<authorization>', 'Content-Type': 'application/json'},
body: JSON.stringify({name: '<string>', description: '<string>', text: '<string>'})
};
fetch('https://app.luly.ai/api/vectors', 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://app.luly.ai/api/vectors",
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([
'name' => '<string>',
'description' => '<string>',
'text' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Content-Type: application/json",
"authorization: <authorization>"
],
]);
$response = curl_exec($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://app.luly.ai/api/vectors"
payload := strings.NewReader("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"text\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("authorization", "<authorization>")
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://app.luly.ai/api/vectors")
.header("authorization", "<authorization>")
.header("Content-Type", "application/json")
.body("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"text\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://app.luly.ai/api/vectors")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["authorization"] = '<authorization>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"text\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"vector_id": "KB-55e64dae-1585-4632-ae97-c909c288c6bc"
}
Usage: Pass the vector_id into your agent’s tools to enable the agent to use the vector store.
"tools": [
"KB-55e64dae-1585-4632-ae97-c909c288c6bc"
]
Headers
Your API key for authentication.
Body
The name of the vector store. Make this a clear name that describes the contents of the store.
A description of the vector store. This can be a longer description of the contents of the store, or what terms to use to search for vectors in the store.This is visible to the AI, so making it descriptive can help the AI understand when to use it or not.
The full text document to be stored and vectorized.
Response
The unique identifier for the vector store.Will start with “KB-”.
{
"vector_id": "KB-55e64dae-1585-4632-ae97-c909c288c6bc"
}
⌘I