Structured Outputs Python Packages

mlx-openai-server

A high-performance API server that provides OpenAI-compatible endpoints for MLX models. Developed using Python and powered by the FastAPI framework, it provides an efficient, scalable, and user-friendly solution for running MLX-based vision and language models locally with an OpenAI-compatible interface.

ironclad-ai

Reliability for LLM agents through enforcement, not model size — Agent-Contract-Kernel + a fail-closed orchestration engine. Model-agnostic. 🇦🇪 Built in the UAE.

justllm

Production LLM calls. Just the three lines. Cross-provider fallback, native caching, and reversible context compression on by default.

cuery

Prompt (cue) management and execution for tabular data.

schemafit

Provider-aware structured-output / JSON-Schema CI linter — fail CI before your schema 400s on OpenAI, Anthropic, or Gemini.

ai-prompt-runner

CLI tool to send prompts to an AI API and save JSON/Markdown outputs.

structured-logprobs

OpenAI's Structured Outputs with Logprobs

truenorth-framework

Declare the outcome, skip the logic. The developer-first infrastructure engine for structured, multi-turn AI conversations with built-in safety, async follow-ups, and native compliance

qwed-open-responses

Verification guards for OpenAI Responses API - Verify AI agent outputs before execution

llmcall

A lite abstraction layer for structured LLM calls

nfield

Extract structured fields from a document at any scale, from a handful to n number.

structllm

Universal Python library for Structured Outputs with any LLM provider

customer-discovery-agent

Scan online communities (Reddit, +) for maker pain points; cluster into a weekly digest.

structured-output-cookbook

Extract structured data from text using LLMs with ready-to-use templates

structuinput

structuinput transforms natural language inputs into structured outputs like API templates, config files, and data schemas, streamlining development and integration.