跳到正文
cccskills
免费在 GitHub 公开

ai-apis

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.

中文简介正在准备中。当前显示原文说明。

集成工具OpenAIElevenLabs
查看安装方法

包含的文件(2)

  • SKILL.md5.3 KB
  • metadata.json1.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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

For all APIs below, use import { fetch } from "expo/fetch". Do not use the openai package. Write logic in ./src/lib/openai.ts.

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-5.1 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-5.1", input: "Your prompt here" }),
});

Streaming: Add stream: true to the body. Parse SSE events from the response body:

const reader = response.body?.getReader();
const decoder = new TextDecoder();
while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  // Parse lines starting with "data: " and look for event.type === "response.output_text.delta"
  // The delta text is in event.delta
}

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-5.1",
    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/

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

[00] TnR ABSOLUTE RIGOR — Systemic Verification Doctrine. Forced cognitive exertion for high-stakes investigations. Mandates absolute deconstruction, mathematical proof chains, and ≥95% derived certainty. Zero-tolerance for heuristics or sentiment-based reasoning. Shortcuts are defined as intentional hallucinations.

中文简介正在准备中。当前显示原文说明。

diegosouzapw/awesome-omni-skill642026年3月2日 更新

2agent

免费

Configures 2-Agent workflow between PM and implementation roles. Use when user mentions 2-Agent, 2エージェント, PM連携設定, Cursor設定, Cursor連携, 2-agent運用. Do NOT load for: 単独運用, ワークフロー実行, ハンドオフ処理.

中文简介正在准备中。当前显示原文说明。

diegosouzapw/awesome-omni-skill642026年3月2日 更新

Appends relevant hashtags to journal entries based on content analysis. Intended for LLM execution.

中文简介正在准备中。当前显示原文说明。

diegosouzapw/awesome-omni-skill642026年3月2日 更新

add-agent

免费

Add a new AI coding agent to Agent Sandbox. Creates all required files (Dockerfile, templates, CI, docs) and wires the agent into the CLI, proxy, and build system.

中文简介正在准备中。当前显示原文说明。

diegosouzapw/awesome-omni-skill642026年3月2日 更新

Add a new property to the AI agents database. Use when the user wants to add, create, or introduce a new column, property, field, or feature to track across all agents in the comparison matrix. Handles all four required steps - database updates, groups.json, table display, and GitHub issue templates.

中文简介正在准备中。当前显示原文说明。

diegosouzapw/awesome-omni-skill642026年3月2日 更新

Add new Agent templates to the meta-agent-skills framework.

中文简介正在准备中。当前显示原文说明。

diegosouzapw/awesome-omni-skill642026年3月2日 更新

查看 diegosouzapw 的全部技能

报告此技能的问题