LLM Structured Outputs Handbook

4 months ago

LLMs mostly produce syntactically valid outputs but can occasionally fail due to their probabilistic nature.
Developers use LLMs programmatically for tasks like data extraction, code generation, and tool calling.
There are deterministic ways to ensure structured LLM outputs.
The handbook covers under-the-hood details, best tools & techniques, and how to pick them.
It also includes building, deploying, scaling systems, optimizing for latency and cost, and improving output quality.
Structured generation is evolving rapidly, making most resources outdated quickly.
The handbook is a regularly updated living document.
It can be read start-to-finish or used as a lookup table.
The maintainers are behind Nanonets-OCR models and docstrange.
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