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New library ShapeCraft tackles AI semantic correctness beyond JSON Schema

A new open-source library called ShapeCraft aims to improve the reliability of AI systems by addressing the limitations of JSON Schema for production use. The library's creator argues that while JSON Schema ensures structural correctness, it does not guarantee semantic accuracy, meaning an LLM can return valid JSON that is factually incorrect or hallucinated. ShapeCraft provides a unified API across multiple LLM providers like OpenAI and Anthropic, exposing the actual guarantee level of their structured output capabilities, which vary significantly. AI

IMPACT Enhances reliability of LLM data extraction by addressing semantic validation gaps beyond structural JSON Schema checks.

RANK_REASON Launch of a new open-source library for LLM structured output.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New library ShapeCraft tackles AI semantic correctness beyond JSON Schema

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Hardik Mehta ·

    Why JSON Schema Isn't Enough for Production AI

    <h1> Your LLM Can Return Perfect JSON and Still Be Completely Wrong </h1> <p>Most developers (including me) assumed one thing when Structured Outputs became available:</p> <blockquote> <p>If my JSON validates against the schema, my extraction is correct.</p> </blockquote> <p>Unfo…