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

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.

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

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.

Repository for our paper "DRS: Deep Question Reformulation With Structured Output".

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 This repository is public because current LLM examples often use outdated API calls, and this script aims to help users quickly experiment with structured outputs.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

ostruct uses OpenAI Structured Output APIs to process a set of plain text files (data, reports, source code, CSV, etc), input variables, a dynamic prompt template, and a JSON schema specifying the desired output format, and will produce the result in JSON format.

This Project transcribes spoken content into text and identifies distinct speakers, organizing the transcript accordingly for easier review and analysis.

A playground to check if structured output works

A simple repository demonstrating LlamaCPP yielding structured output

Dagster pipeline for extracting text from PDFs, generating structured data via OpenAI, and storing in PostgreSQL.