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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

Deterministic stateless multi-provider AI prompt runner for CLI, scripts, and CI workflows with contract-driven structured outputs.

llmcall

A lite abstraction layer for structured LLM calls

structured-output-cookbook

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

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.