> For the complete documentation index, see [llms.txt](https://infronai.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://infronai.gitbook.io/docs/llm-inference-handbook/llm-inference-advanced/unified-api-compatibility.md).

# Unified API compatibility

This documentation systematically introduces the core concepts and practical methods of unified API compatibility in LLM inference, covering three essential topics:

**OpenAI-Compatible API**: Explains how the OpenAI API has become the de facto industry standard and how compatible interfaces enable seamless model migration while reducing vendor lock-in. Developers can switch between self-hosted models, open-source solutions, and different inference providers by simply changing the endpoint URL, without rewriting application logic.

**Structured Outputs**: Provides comprehensive guidance on generating machine-parseable formats like JSON and XML from LLMs instead of free-form text. The documentation compares three mainstream implementation approaches—native model API support, re-prompting with validation, and constrained decoding—helping developers choose optimal solutions for various scenarios, from information extraction to agent orchestration, enabling reliable automation workflows.

**Function Calling**: (This section was not fully loaded on the original page) Addresses how models understand and invoke external tools and APIs, a critical capability for building AI agents and complex applications.


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