MLX Omni Server is a local inference server powered by Apple's MLX framework, specifically designed for Apple Silicon (M-series) chips. It implements OpenAI-compatible API endpoints, enabling seamless integration with existing OpenAI SDK clients while leveraging the power of local ML inference.

A versatile workflow automation platform to create, organize, and execute AI workflows, from a single LLM to complex AI-driven workflows.

Simplifies the retrieval, extraction, and training of structured data from various unstructured sources.

Schema-Guided Reasoning (SGR) is a technique that guides large language models (LLMs) to produce structured, clear, and predictable outputs by enforcing reasoning through predefined steps. By creating a specific schema (or structured template), you explicitly define:

This repository demonstrates how to leverage OpenAI's GPT-4 models with JSON Strict Mode to extract structured data from web pages. It combines web scraping capabilities from Firecrawl with OpenAI's advanced language models to create a powerful data extraction pipeline.

Code from the ODSC Agentic Graph RAG workshop combining vector, FTS & graph retrieval for RAG. Includes observability and guardrails for evaluating outputs.

🔍Declarative LLM-powered analyzer for security events and system logs. Extracts, structures, and visualizes data for Kibana/Elasticsearch.

Better LLMs Structured Outputs - A useful python package!

Python for logic. English for intelligence.

[ACL 2025] Repository for our paper "DRS: Deep Question Reformulation With Structured Output".

Schema-first AI analysis CLI that transforms messy data into structured insights. Define your output format, get guaranteed JSON results from any source. Combines OpenAI models with multi-tool orchestration (Code Interpreter, File Search, Web Search, MCP) for AI-powered data synthesis.

Python decorator to define GPT-powered functions on top of OpenAI's structured output

Structured Output OpenAI Showcase. A Prime Numbers Calculator that demonstrates OpenAI's structured output capabilities. This repository is public because current LLM examples often use outdated API calls, and this script aims to help users quickly experiment with structured outputs.

This is the Python backend for InsightAI

Universal Python library for Structured Outputs with any LLM provider

This repository demonstrates how to use OpenAI's Response API (with GPT-4.1 and tool calling) to extract the main product image URL from an e-commerce product page. It provides both Python and TypeScript implementations, returning a structured output for easy integration.

This repository contains examples for learning Google's Agent Development Kit (ADK), a powerful framework for building LLM-powered agents.

Enter cricket activity log (fitness, coaching, match, rest day) through voice interface. Get insights on historical data.

Control LLM token generation by directly manipulating logits to enforce structured outputs. Built with Hugging Face Transformers and demonstrated using Qwen2.5-0.5B.