openai-api

Integrate OpenAI stateless APIs for chat, voice, batch, embeddings, images, audio, and TTS.

Updated Jan 29, 2026
One-click install
npx skills add https://github.com/brendadeeznuts1111/tier-1380-omega --skill openai-api-brendadeeznuts1111
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: openai-api
Source: https://github.com/brendadeeznuts1111/tier-1380-omega/tree/main/skills/openai-api
Command: npx skills add https://github.com/brendadeeznuts1111/tier-1380-omega --skill openai-api-brendadeeznuts1111

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, and includes scripts (resource) and references (resource) and templates (resource) components.

What problem does it solve?

This Skill empowers developers to integrate OpenAI's powerful stateless APIs, including Chat Completions (GPT-5.2, o3), Realtime voice, Embeddings, DALL-E 3, Whisper, and TTS, into their applications efficiently.

Core Features & Use Cases

  • Chat Completions: Implement conversational AI, text generation, function calling, and structured outputs with the latest GPT models.
  • Embeddings: Generate vector embeddings for semantic search and RAG (Retrieval-Augmented Generation).
  • Images & Audio: Create images with DALL-E 3 and process audio with Whisper transcription and TTS.
  • Error Handling: Prevents common API errors like rate limits (429), invalid keys, and model mismatches.
  • Use Case: Quickly build a chatbot that uses GPT-5.2 for responses, generates embeddings for a knowledge base, and creates audio summaries of the conversation.

Quick Start

Use the openai-api skill to generate an image of a futuristic city at sunset.

Frequently Asked Questions about openai-api

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate OpenAI API for chat completions and generate text using GPT-5.2?

OpenAI API integration for chat completions involves sending requests to GPT-5.2 or o3 models to handle conversational AI, text generation, and function calling. This stateless approach returns structured outputs directly for your application workflows.

What's the best way to generate vector embeddings for a RAG knowledge base?

Generating vector embeddings for RAG involves passing text data to the OpenAI API to create numerical vectors. These stateless API outputs enable semantic search and Retrieval-Augmented Generation within your AI applications.

How do I handle rate limit errors when calling OpenAI APIs?

Handling OpenAI API rate limit errors requires implementing error management for HTTP 429 responses. The integration provides error handling logic to prevent rate limits, invalid key rejections, and model compatibility issues from disrupting your application workflows.

Can I use the OpenAI API to generate images with DALL-E 3 and transcribe audio with Whisper?

Yes, the OpenAI API supports generating images with DALL-E 3 and transcribing audio with Whisper. The integration covers these stateless APIs alongside TTS speech synthesis, allowing you to process visual and audio inputs within a single workflow.

Does batch processing OpenAI API calls reduce costs for large-scale text generation?

Batch processing OpenAI API calls reduces costs for large-scale text generation. Grouping multiple chat completion or embedding requests together achieves cost savings compared to processing each stateless API request individually.