1import OpenAI from "openai";
2
3const client = new OpenAI({
4  apiKey: "your-api-key",
5  baseURL: "https://api.nebux.cloud/v1",
6});

7const completion = await client.chat.completions.create({
8  model: "qwen3-14b",
9  messages: [
10    { role: "system", content: "You are a helpful assistant." },
11    { role: "user", content: "Recommend me a book" },
12    { role: "assistant", content: "Try The Shadow of the Wind" },
13    { role: "user", content: "And a similar one?" },
14  ],
15});
16
17console.log(completion.choices[0].message.content);

7const stream = await client.chat.completions.create({
8  model: "qwen3-14b",
9  messages: [{ role: "user", content: "Which running shoes do you recommend?" }],
10  stream: true,
11});
12
13for await (const chunk of stream) {
14  process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
15}

7const completion = await client.chat.completions.create({
8  model: "qwen3-14b",
9  messages: [
10    { role: "system", content: "Classify each comment as good or bad, keeping its id. Reply as JSON." },
11    { role: "user", content: "1: Great! 2: Awful 3: Good 4: Slow" },
12  ],
13  response_format: { type: "json_object" },
14});
15
16console.log(JSON.parse(completion.choices[0].message.content));

7const res = await client.chat.completions.create({
8  model: "qwen3-14b",
9  messages: [
10    { role: "user", content: "A coffee is 1.20. What are 7 with 15% off?" },
11  ],
12  // chat_template_kwargs is outside the OpenAI library's types,
13  // so it travels as an extra request parameter.
14  // The other option is calling POST https://api.nebux.cloud/v1/chat/completions
15  // directly.
16  // @ts-expect-error
17  chat_template_kwargs: {"enable_thinking": true},
18});
19
20console.log(res.choices[0].message.content);

7const res = await client.chat.completions.create({
8  model: "qwen3-14b",
9  messages: [
10    { role: "user", content: "Describe the product in one line" },
11  ],
12  temperature: 0.7,
13  max_tokens: 1024,
14  top_p: 0.95,
15  frequency_penalty: 0.4,
16  stop: ["\n\n"],
17});
18
19console.log(res.choices[0].message.content);

7const res = await client.chat.completions.create({
8  model: "qwen3-14b",
9  messages: [
10    { role: "user", content: "Classify this review" },
11  ],
12  temperature: 0,
13  seed: 42,
14});
15
16console.log(res.choices[0].message.content);

7const completion = await client.chat.completions.create({
8  model: "qwen3-14b",
9  messages: [{ role: "user", content: "What's the weather in València?" }],
10  tools: [
11    {
12      type: "function",
13      function: {
14        name: "get_weather",
15        description: "Get the current weather for a location",
16        parameters: {
17          type: "object",
18          properties: { location: { type: "string" } },
19          required: ["location"],
20        },
21      },
22    },
23  ],
24});
25
26console.log(completion.choices[0].message.tool_calls);