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.

cuery

Prompt (cue) management and execution for tabular data.

structured-logprobs

OpenAI's Structured Outputs with Logprobs

ai-prompt-runner

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

llmcall

A lite abstraction layer for structured LLM calls

customer-discovery-agent

🔍 Reddit pain-point scraper + Claude clustering. Find what users actually complain about, structured outputs. MIT.

structured-output-cookbook

Fast structured data extraction from text using LLMs. Pre-built templates for common use cases + custom schema support.

qwed-open-responses

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

structllm

Universal Python library for Structured Outputs with any LLM provider

structuinput

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