github.com/LogCreative/PGFPlotsEdt @4.5

PGFPlotsEdt - Faster to PGFPlot in LaTeX

A PGFPlots Statistic Graph Interactive Editor.

Online website | Documentation | Video | 网站(简体中文) | 文档(简体中文) | 视频(简体中文)

Introduction

PGFPlots is a remarkable package in LaTeX, to create precise, vectorized, and highly personalized statistic graphs. You could get more information about PGFPlots package on https://github.com/pgf-tikz/pgfplots, thank all those contributors for creating a useful package to plot in LaTeX natively.

PGFPlotsEdt is basically a frontend for this package, to generate PGFPlots code automatically through a web-based user interface. This project is under LaTeX Sparkle Project, you could also get some tips on PGFPlots on this webpage.

TikzEdt is the inspiration of this project, to create LaTeX TikZ graph in WYSIWYG (what you see is what you get) mode. You could download this software on TikzEdt homepage, you could also get more tips on TikZEdt on this webpage.

Usage

• Online version You could use the online version directly:

  https://logcreative.github.io/PGFPlotsEdt/

  

• Deployment version PGFPlotsEdt also provides several local deployment methods for faster compilation and other features, refer to the documentation for details:

• Open locally: open index.html in the browser.
• Local compilation: use ppedt_server.py to compile standalone tex files locally in near real-time (see pgfplots-benchmark repo for details).
• LLM: use ppedt_server_llm.py to enable code completion with Llama 3.
• Deployment compilation: use deploy/gunicorn-deploy.py for production use to serve multiple users.

Documentation

This repo contains documentation in Markdown format, which could be compiled into PDFs through l3build doc in the folder. The generated PDFs are automatically updated in PGFPlotsEdt-doc repo.

Welcome to contribute your translation to PGFPlotsEdt! See CONTRIBUTING for details.

Acknowledgements

Vue.js is the progressive JavaScript framework for this project.

LaTeXOnline is the chosen online LaTeX compiler for previewing the graph result.

MathJax is the TeX typeset rendering machine for previewing the formula input.

Llama 3 or GLM-4.6 is the chosen large language model to generate code. The local LLM model is deployed by MLC LLM. The serverless LLM model is provided by Cloudflare. The RAG framework is provided by llama-index.

Copyright (c) 2020-2025 Log Creative & LaTeX Sparkle Project