ai-apis

name	ai-apis
description	How to use AI APIs like OpenAI, ChatGPT, Elevenlabs, etc. When a user asks you to make an app that requires an AI API, use this skill to understand how to use the API or how to respond to the user.

ai-apis-like-chatgpt

Instructions

The Vibecode Enviroment comes pre-installed with a lot of AI APIs like OpenAI, ChatGPT, Elevenlabs, etc. You can use these APIs to generate text, images, videos, sounds, etc.

Users can find most of the APIs in the API tab of the Vibecode App. You can tell the user to look there for any custom or advanced API integrations.

However, we will go over the basic OpenAI APIs.

Examples

Responses API (Generate text, analyze images, search the web)

You can use the OpenAI Responses API to generate text, search the web, and analyze images. The latest model family is gpt-5.2 as of December 2025. Docs: https://platform.openai.com/docs/api-reference/responses/create

Basic request:

const response = await fetch("https://api.openai.com/v1/responses", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: `Bearer ${process.env.EXPO_PUBLIC_VIBECODE_OPENAI_API_KEY}`,
  },
  body: JSON.stringify({ model: "gpt-5.2", input: "Your prompt here" }),
});

Vision (Image Analysis): Use expo-image-picker to select images. You must use expo-file-system to read as base64 data URL:

import * as ImagePicker from "expo-image-picker";
import * as FileSystem from "expo-file-system";

// Pick image from library
const result = await ImagePicker.launchImageLibraryAsync({
  mediaTypes: ["images"],
  allowsEditing: true,
  quality: 0.8,
});
if (result.canceled) return;
const imageUri = result.assets[0].uri;

// Read as base64 and build data URL
const base64 = await FileSystem.readAsStringAsync(imageUri, {
  encoding: FileSystem.EncodingType.Base64,
});
const mimeType = imageUri.endsWith(".png") ? "image/png" : "image/jpeg";
const dataUrl = `data:${mimeType};base64,${base64}`;

// Send to vision API
const response = await fetch("https://api.openai.com/v1/responses", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: `Bearer ${process.env.EXPO_PUBLIC_VIBECODE_OPENAI_API_KEY}`,
  },
  body: JSON.stringify({
    model: "gpt-5.2",
    input: [{
      role: "user",
      content: [
        { type: "input_text", text: "What's in this image?" },
        { type: "input_image", image_url: dataUrl },
      ],
    }],
  }),
});

Image Generation API (Generate images)

Model: gpt-image-1. Docs: https://platform.openai.com/docs/api-reference/images/create

const response = await fetch("https://api.openai.com/v1/images/generations", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: `Bearer ${process.env.EXPO_PUBLIC_VIBECODE_OPENAI_API_KEY}`,
  },
  body: JSON.stringify({
    model: "gpt-image-1",
    prompt: "A cute baby sea otter",
    n: 1,
    size: "1024x1024",
  }),
});
const data = await response.json();
const imageUrl = data.data[0].url; // or data.data[0].b64_json for base64

Image Edit API (Edit images)

Model: gpt-image-1. Docs: https://platform.openai.com/docs/api-reference/images/createEdit

Use File from expo-file-system/next and .blob() for FormData (same pattern as audio):

import { File } from "expo-file-system/next";

const file = new File(imageUri);
const blob = await file.blob();

const formData = new FormData();
formData.append("image", blob, file.name);
formData.append("prompt", "Add a hat to the person");
formData.append("model", "gpt-image-1");
formData.append("n", "1");
formData.append("size", "1024x1024");

const response = await fetch("https://api.openai.com/v1/images/edits", {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.EXPO_PUBLIC_VIBECODE_OPENAI_API_KEY}` },
  body: formData,
});
const data = await response.json();
const editedImageUrl = data.data[0].url;

Audio Transcription API (Transcribe audio)

Model: gpt-4o-transcribe. Docs: https://platform.openai.com/docs/api-reference/audio/create

React Native FormData with expo/fetch: Use File from expo-file-system/next and call .blob():

import { File } from "expo-file-system/next";

const file = new File(audioUri); // audioUri from expo-av recording
const blob = await file.blob();

const formData = new FormData();
formData.append("file", blob, file.name);
formData.append("model", "gpt-4o-transcribe");

const response = await fetch("https://api.openai.com/v1/audio/transcriptions", {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.EXPO_PUBLIC_VIBECODE_OPENAI_API_KEY}` },
  body: formData,
});
const data = await response.json();
const transcription = data.text;

Recording audio: Use expo-av to record. See: https://docs.expo.dev/versions/latest/sdk/av/