curl --request POST \
  --url https://api.mixroute.ai/v1/chat/completions \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-5.5",
    "messages": [
      {"role": "system", "content": "你是一个有用的助手"},
      {"role": "user", "content": "请用中文简要介绍人工智能"}
    ],
    "temperature": 0.7
  }'

from openai import OpenAI

client = OpenAI(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai/v1"
)

response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[
        {"role": "system", "content": "你是一个有用的助手"},
        {"role": "user", "content": "请用中文简要介绍人工智能"}
    ],
    temperature=0.7
)
print(response.choices[0].message.content)

const OpenAI = require('openai');

const client = new OpenAI({
  apiKey: 'sk-xxxxxxxxxx',
  baseURL: 'https://api.mixroute.ai/v1'
});

const response = await client.chat.completions.create({
  model: 'gpt-5.5',
  messages: [
    { role: 'system', content: '你是一个有用的助手' },
    { role: 'user', content: '请用中文简要介绍人工智能' }
  ],
  temperature: 0.7
});
console.log(response.choices[0].message.content);

<?php
$client = new GuzzleHttp\Client();
$response = $client->post('https://api.mixroute.ai/v1/chat/completions', [
    'headers' => [
        'Authorization' => 'Bearer sk-xxxxxxxxxx',
        'Content-Type' => 'application/json',
    ],
    'json' => [
        'model' => 'gpt-5.5',
        'messages' => [
            ['role' => 'system', 'content' => '你是一个有用的助手'],
            ['role' => 'user', 'content' => '请用中文简要介绍人工智能']
        ],
        'temperature' => 0.7
    ]
]);
echo $response->getBody();

package main

import (
    "context"
    "fmt"
    openai "github.com/sashabaranov/go-openai"
)

func main() {
    config := openai.DefaultConfig("sk-xxxxxxxxxx")
    config.BaseURL = "https://api.mixroute.ai/v1"
    client := openai.NewClientWithConfig(config)

    resp, _ := client.CreateChatCompletion(
        context.Background(),
        openai.ChatCompletionRequest{
            Model: "gpt-5.5",
            Messages: []openai.ChatCompletionMessage{
                {Role: "system", Content: "你是一个有用的助手"},
                {Role: "user", Content: "请用中文简要介绍人工智能"},
            },
        },
    )
    fmt.Println(resp.Choices[0].Message.Content)
}

import com.theokanning.openai.OpenAiService;
import com.theokanning.openai.completion.chat.*;

OpenAiService service = new OpenAiService("sk-xxxxxxxxxx");
ChatCompletionRequest request = ChatCompletionRequest.builder()
    .model("gpt-5.5")
    .messages(Arrays.asList(
        new ChatMessage("system", "你是一个有用的助手"),
        new ChatMessage("user", "请用中文简要介绍人工智能")
    ))
    .temperature(0.7)
    .build();
ChatCompletionResult result = service.createChatCompletion(request);
System.out.println(result.getChoices().get(0).getMessage().getContent());

require 'openai'

client = OpenAI::Client.new(
  access_token: 'sk-xxxxxxxxxx',
  uri_base: 'https://api.mixroute.ai/v1'
)

response = client.chat(
  parameters: {
    model: 'gpt-5.5',
    messages: [
      { role: 'system', content: '你是一个有用的助手' },
      { role: 'user', content: '请用中文简要介绍人工智能' }
    ],
    temperature: 0.7
  }
)
puts response.dig('choices', 0, 'message', 'content')

{
  "id": "chatcmpl-xxx",
  "object": "chat.completion",
  "created": 1234567890,
  "model": "gpt-5.5",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "人工智能是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 25,
    "completion_tokens": 100,
    "total_tokens": 125
  }
}