Python:
import os
import requests

class APIClient:
    def __init__(self, api_key: str, api_secret: str, base_url: str = "https://univie-api.academic-ai.at"):
        self.api_key = api_key
        self.api_secret = api_secret
        self.base_url = base_url

    def create_chat_completion(self, model: str, messages: list, **kwargs):
        url = f"{self.base_url}/api/v1/llm/chat"
        headers = {
            "X-Client-ID": self.api_key,
            "X-Client-Secret": self.api_secret,
            "Content-Type": "application/json",
        }
        payload = {
            "model": model,
            "messages": messages,
            **kwargs,
        }

        response = requests.post(url, headers=headers, json=payload, timeout=30)
        response.raise_for_status()
        return response.json()


# Load credentials from environment variables (recommended)
# Set these in your environment or .env file:
#   CLIENT_ID=your-client-id-here
#   CLIENT_SECRET=your-secret-here
api = APIClient(
    api_key=os.environ["CLIENT_ID"],
    api_secret=os.environ["CLIENT_SECRET"],
)

response = api.create_chat_completion(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello, how can you help me?"}],
    temperature=0.7,
    maxTokens=1000,
)
print(f"Response: {response['data']['content']}")
print(f"Tokens used: {response['data']['usage']['totalTokens']}")

Typescript:
class APIClient {
  private apiKey: string;
  private apiSecret: string;
  private baseUrl: string;

  constructor(
    apiKey: string,
    apiSecret: string,
    baseUrl: string = "https://univie-api.academic-ai.at"
  ) {
    this.apiKey = apiKey;
    this.apiSecret = apiSecret;
    this.baseUrl = baseUrl;
  }

  async createChatCompletion(
    model: string,
    messages: Array<{ role: string; content: string }>,
    options: Record<string, any> = {}
  ) {
    const url = `${this.baseUrl}/api/v1/llm/chat`;

    const headers = {
      "X-Client-ID": this.apiKey,
      "X-Client-Secret": this.apiSecret,
      "Content-Type": "application/json",
    };

    const payload = {
      model,
      messages,
      ...options,
    };

    const res = await fetch(url, {
      method: "POST",
      headers,
      body: JSON.stringify(payload),
    });

    if (!res.ok) {
      throw new Error(`Request failed: ${res.status}`);
    }

    return res.json();
  }
}

// Load credentials from environment variables (recommended)
// Set these in your environment or .env file:
//   CLIENT_ID=your-client-id-here
//   CLIENT_SECRET=your-secret-here
const api = new APIClient(
  process.env.CLIENT_ID!,
  process.env.CLIENT_SECRET!,
);

api
  .createChatCompletion(
    "gpt-4o",
    [{ role: "user", content: "Hello, how can you help me?" }],
    { temperature: 0.7, maxTokens: 1000 }
  )
  .then((response) => {
    console.log(`Response: ${response.data.content}`);
    console.log(`Tokens used: ${response.data.usage.totalTokens}`);
  })
  .catch(console.error);