LLM API integration is the process of connecting applications to large language model providers through standardized interfaces, enabling developers to leverage AI capabilities without managing infrastructure. Modern LLM APIs offer unified OpenAI-compatible formats across an expanding provider landscape—now including OpenAI's GPT-5 family, Anthropic Claude, Google Gemini 2.5, xAI Grok, and many others—with sophisticated streaming, function calling, and agentic tooling. OpenAI's Responses API has displaced the deprecated Assistants API as the recommended endpoint for stateful, multi-tool workflows, while built-in tools like web search and file search reduce custom integration overhead. The key challenge lies not in calling a single API, but in building resilient, observable, and cost-effective systems that handle rate limits, fallbacks, context management, multi-provider routing, and LLM-specific security threats such as prompt injection—skills that separate prototype AI apps from production-grade deployments.
What This Cheat Sheet Covers
This topic spans 13 focused tables and 129 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Major LLM API Providers
| Provider | Example | Description |
|---|---|---|
POST /v1/chat/completions | • Industry-standard API powering GPT-5 family (GPT-5, GPT-5.4, GPT-5-mini) • offers Chat Completions, Responses API, function calling, vision, streaming, and fine-tuning | |
claude-sonnet-4-6 | • Claude models with extended context (up to 1M tokens), tool use, and prompt caching • strong reasoning and safety features | |
gemini-2.5-pro | • Multimodal API with vision, audio, code execution • Gemini 2.5 Flash optimized for speed and cost, Pro for complex reasoning | |
https://api.x.ai/v1 | • OpenAI-compatible endpoint for Grok models • 2M token context window, built-in real-time web search via X | |
command-r+, embed-v4 | • Enterprise-focused with Command (generation), Embed (embeddings), and Rerank models • multilingual and RAG-optimized | |
Regional deployments with PTUs | Microsoft-hosted OpenAI models with enterprise security, private networking, RBAC, and provisioned throughput units for guaranteed capacity |