curl --request POST \
  --url https://direct.evolink.ai/v1/messages \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "evolink/auto",
  "messages": [
    {
      "role": "user",
      "content": "介绍一下人工智能的发展历史"
    }
  ],
  "max_tokens": 1024,
  "temperature": 0.7,
  "top_p": 0.9,
  "top_k": 40,
  "stream": false
}
'

import requests

url = "https://direct.evolink.ai/v1/messages"

payload = {
    "model": "evolink/auto",
    "messages": [
        {
            "role": "user",
            "content": "介绍一下人工智能的发展历史"
        }
    ],
    "max_tokens": 1024,
    "temperature": 0.7,
    "top_p": 0.9,
    "top_k": 40,
    "stream": False
}
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: 'evolink/auto',
    messages: [{role: 'user', content: '介绍一下人工智能的发展历史'}],
    max_tokens: 1024,
    temperature: 0.7,
    top_p: 0.9,
    top_k: 40,
    stream: false
  })
};

fetch('https://direct.evolink.ai/v1/messages', 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://direct.evolink.ai/v1/messages",
  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' => 'evolink/auto',
    'messages' => [
        [
                'role' => 'user',
                'content' => '介绍一下人工智能的发展历史'
        ]
    ],
    'max_tokens' => 1024,
    'temperature' => 0.7,
    'top_p' => 0.9,
    'top_k' => 40,
    'stream' => false
  ]),
  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://direct.evolink.ai/v1/messages"

	payload := strings.NewReader("{\n  \"model\": \"evolink/auto\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"介绍一下人工智能的发展历史\"\n    }\n  ],\n  \"max_tokens\": 1024,\n  \"temperature\": 0.7,\n  \"top_p\": 0.9,\n  \"top_k\": 40,\n  \"stream\": false\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://direct.evolink.ai/v1/messages")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"evolink/auto\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"介绍一下人工智能的发展历史\"\n    }\n  ],\n  \"max_tokens\": 1024,\n  \"temperature\": 0.7,\n  \"top_p\": 0.9,\n  \"top_k\": 40,\n  \"stream\": false\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://direct.evolink.ai/v1/messages")

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\": \"evolink/auto\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"介绍一下人工智能的发展历史\"\n    }\n  ],\n  \"max_tokens\": 1024,\n  \"temperature\": 0.7,\n  \"top_p\": 0.9,\n  \"top_k\": 40,\n  \"stream\": false\n}"

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

{
  "id": "msg_01XFDUDYJgAACyzWYzeHhsX7",
  "model": "gpt-5.4",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "人工智能的发展历史可以追溯到20世纪50年代..."
    }
  ],
  "usage": {
    "input_tokens": 15,
    "output_tokens": 156
  }
}