curl --request POST \
  --url https://api.xpander.ai/v1/agents/{agent_id}/conversations/invoke \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data @- <<EOF
{
  "input": {
    "text": "Summarize today's signups.",
    "user": {
      "id": "user-123",
      "email": "you@example.com"
    }
  }
}
EOF

import requests

url = "https://api.xpander.ai/v1/agents/{agent_id}/conversations/invoke"

payload = { "input": {
        "text": "Summarize today's signups.",
        "user": {
            "id": "user-123",
            "email": "you@example.com"
        }
    } }
headers = {
    "x-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-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    input: {
      text: 'Summarize today\'s signups.',
      user: {id: 'user-123', email: 'you@example.com'}
    }
  })
};

fetch('https://api.xpander.ai/v1/agents/{agent_id}/conversations/invoke', 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.xpander.ai/v1/agents/{agent_id}/conversations/invoke",
  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' => [
        'text' => 'Summarize today\'s signups.',
        'user' => [
                'id' => 'user-123',
                'email' => 'you@example.com'
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-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.xpander.ai/v1/agents/{agent_id}/conversations/invoke"

	payload := strings.NewReader("{\n  \"input\": {\n    \"text\": \"Summarize today's signups.\",\n    \"user\": {\n      \"id\": \"user-123\",\n      \"email\": \"you@example.com\"\n    }\n  }\n}")

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

	req.Header.Add("x-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.xpander.ai/v1/agents/{agent_id}/conversations/invoke")
  .header("x-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"input\": {\n    \"text\": \"Summarize today's signups.\",\n    \"user\": {\n      \"id\": \"user-123\",\n      \"email\": \"you@example.com\"\n    }\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.xpander.ai/v1/agents/{agent_id}/conversations/invoke")

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

request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"input\": {\n    \"text\": \"Summarize today's signups.\",\n    \"user\": {\n      \"id\": \"user-123\",\n      \"email\": \"you@example.com\"\n    }\n  }\n}"

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

{
  "id": "7a7a7a7a-1111-2222-3333-555555555555",
  "agent_id": "a1a1a1a1-b2b2-c3c3-d4d4-e5e5e5e5e5e5",
  "organization_id": "0a0a0a0a-1b1b-2c2c-3d3d-4e4e4e4e4e4e",
  "status": "completed",
  "input": {
    "text": "Summarize today's signups.",
    "user": {
      "id": "user-123",
      "email": "you@example.com"
    }
  },
  "result": "42 new signups today, up 12% week over week.",
  "created_at": "2026-07-28T20:59:02.915959Z",
  "finished_at": "2026-07-28T20:59:51.661537Z",
  "llm_model_provider": "anthropic",
  "llm_model_name": "claude-sonnet-5",
  "tokens": {
    "input_tokens": 70216,
    "output_tokens": 3496,
    "total_tokens": 73712
  },
  "parent_execution": "f0f0f0f0-1111-2222-3333-444444444444",
  "conversation_id": "f0f0f0f0-1111-2222-3333-444444444444",
  "is_gateway": false
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}