Popular GitHub Repositories for Json Atomic

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

? Token-Oriented Object Notation – JSON for LLMs at half the token cost

Structured Text Generation

A curated set of 200 plug-and-play n8n workflows that fuse classic automation with today’s AI stack—vector DBs, embeddings, and LLMs. Import any JSON, add your creds, hit Activate, and you’re live. Built to demo, prototype, or drop straight into production.

JavaScript 对象的差异比较与修补

A python module to repair invalid JSON from LLMs

Document (PDF, Word, PPTX ...) extraction and parse API using state of the art modern OCRs + Ollama supported models. Anonymize documents. Remove PII. Convert any document or picture to structured JSON or Markdown

Resource list for generating JSON using LLMs via function calling, tools, CFG. Libraries, Models, Notebooks, etc.

Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level

The AI-native hybrid search database for modern AI apps

The Declarative Data Generator

Zero-boilerplate REST API framework for PHP 8+. Auto-generates routes, docs, validation.

Extract and convert data from any document, images, pdfs, word doc, ppt or URL into multiple formats (Markdown, JSON, CSV, HTML) with intelligent structured data extraction and advanced OCR.

A fast, lightweight web framework in C for building modern web applications

A fast terminal Excel viewer with an interactive TUI. Features full-text search, formula display, lazy loading for large files, clipboard support, and export to CSV/JSON. Built with Rust and ratatui.

A script to effortlessly extract your entire ChatGPT data export from JSON files to nicely-formatted markdown files.

TONL (Token-Optimized Notation Language)

The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output. Works also with models not fine-tuned to JSON output and function calls.

Integrate LLM in any pipeline - fit/predict pattern, JSON driven flows, and built in concurency support.

Named Entity Recognition (NER) Annotation tool for SpaCy. Generates Traning Data as a JSON which can be readily used.