Node.js（OpenAI SDK）

安装与初始化

npm install openai

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://vip.zen-ai.top/v1",
  apiKey: process.env.VIP_API_KEY, // 建议从环境变量读取
});

也可以设置环境变量 OPENAI_BASE_URL 和 OPENAI_API_KEY，代码中直接 new OpenAI()。

不要在浏览器端直接使用密钥

前端代码中的密钥会被任何访问者看到。请在服务端（Node.js、Serverless 函数等）调用，由你的服务端转发给前端。

基础对话

const resp = await client.chat.completions.create({
  model: "gpt-4.1-mini",
  messages: [
    { role: "system", content: "你是一个简洁的助手。" },
    { role: "user", content: "HTTP 和 HTTPS 有什么区别？" },
  ],
});
console.log(resp.choices[0].message.content);

流式输出

const stream = await client.chat.completions.create({
  model: "gpt-4.1-mini",
  messages: [{ role: "user", content: "讲一个 100 字的小故事" }],
  stream: true,
});
for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}

图片理解

import { readFile } from "node:fs/promises";

const b64 = (await readFile("photo.jpg")).toString("base64");

const resp = await client.chat.completions.create({
  model: "gpt-4.1-mini",
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "图片里有什么？" },
        { type: "image_url", image_url: { url: `data:image/jpeg;base64,${b64}` } },
      ],
    },
  ],
});
console.log(resp.choices[0].message.content);

Responses API

const resp = await client.responses.create({
  model: "gpt-5.5",
  reasoning: { effort: "low" },
  input: "用一句话解释量子纠缠",
});
console.log(resp.output_text);

向量

const resp = await client.embeddings.create({
  model: "text-embedding-3-small",
  input: ["今天天气真好", "The weather is nice today"],
});
console.log(resp.data.map((d) => d.embedding.length));

图像生成

import { writeFile } from "node:fs/promises";

const resp = await client.images.generate({
  model: "gpt-image-1.5",
  prompt: "一只戴着宇航员头盔的柴犬，赛博朋克风格",
  size: "1024x1024",
});
const img = resp.data[0];
if (img.b64_json) await writeFile("dog.png", Buffer.from(img.b64_json, "base64"));
else console.log(img.url);

语音合成与识别

import fs from "node:fs";
import { writeFile } from "node:fs/promises";

// 文本转语音
const speech = await client.audio.speech.create({
  model: "gpt-4o-mini-tts",
  voice: "alloy",
  input: "你好，欢迎使用语音合成服务。",
});
await writeFile("speech.mp3", Buffer.from(await speech.arrayBuffer()));

// 语音转文字
const result = await client.audio.transcriptions.create({
  model: "gpt-4o-mini-transcribe",
  file: fs.createReadStream("speech.mp3"),
});
console.log(result.text);

不使用 SDK（fetch）

Node.js 18+ 内置 fetch，可以直接解析 SSE 流：

const res = await fetch("https://vip.zen-ai.top/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.VIP_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "gpt-4.1-mini",
    stream: true,
    messages: [{ role: "user", content: "你好" }],
  }),
});

const decoder = new TextDecoder();
let buffer = "";
for await (const chunk of res.body) {
  buffer += decoder.decode(chunk, { stream: true });
  const lines = buffer.split("\n");
  buffer = lines.pop();
  for (const line of lines) {
    if (!line.startsWith("data: ")) continue;
    const data = line.slice(6).trim();
    if (data === "[DONE]") continue;
    const json = JSON.parse(data);
    process.stdout.write(json.choices?.[0]?.delta?.content ?? "");
  }
}