json-schema

FastAPI framework, high performance, easy to learn, fast to code, ready for production

Data validation using Python type hints

SQL databases in Python, designed for simplicity, compatibility, and robustness.

A React component for building Web forms from JSON Schema.

The fastest JSON schema Validator. Supports JSON Schema draft-04/06/07/2019-09/2020-12 and JSON Type Definition (RFC8927)

Generate types and converters from JSON, Schema, and GraphQL

📱🚀 🧩 Cross Device & High Performance Normal Form/Dynamic(JSON Schema) Form/Form Builder -- Support React/React Native/Vue 2/Vue 3

Generate Java types from JSON or JSON Schema and annotate those types for data-binding with Jackson, Gson, etc

Super-fast/easy runtime validators and serializers via transformation

Repair malformed JSON from LLMs, APIs, logs, and user input in Python.

Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level

MDA Open Spec — a Markdown superset for agent-facing documents. One .mda source compiles to drop-in SKILL.md, AGENTS.md, MCP-SERVER.md, and CLAUDE.md. JSON Schema validated, with typed dependency graph, footnote relationships, and Sigstore-anchored signatures. For agentskills.io and AAIF runtimes.

A universal, industry-neutral taxonomy of cognitive core skills (perception, memory, reasoning, planning, action, verification, learning, governance) for LLMs, SLMs, AI agents, and world models — with schemas, 159 skill cards, benchmarks, and CI.

Python library for the instruction and reliable validation of structured outputs (JSON) of Large Language Models (LLMs) with Ollama and Pydantic. -> Deterministic work with LLMs.

Turn documents into structured JSON with local-first document AI. Run 100% locally by default, with API, CLI, and Web UI.

Bounded, inspectable LLM inference pipelines from declared YAML — runs offline against Ollama or any OpenAI-compatible local server, emitting JSONL traces, inspect reports, and stable exit codes.

Validate and retry LLM outputs for ruby_llm. Describe the JSON response you expect, fall back to a stronger model when the cheaper one fails the rules, and gate CI on regressions — all as one contract object per step.

OpenAI-compatible bridge that exposes Codex CLI/SDK as /v1/chat/completions with multimodal + JSON schema