Today, we are talking about Gigningestan extension for your browser which transforms any github deposit into a perfectly digestible text format for LLM (large Models).

The 1st thing to know is that this extension fits directly into your browser (Chrome, Firefox or Edge) and adds an “Open in Gingingest” button on the Github deposits. A single click is enough to transform all the source code into an optimized format for prompt.

SCR 20250121 Hzal 2

But what exactly is it for?

Well, imagine that you want to have an open source project analyzed by an AI or even have it generated documentation automatically? And why not obtain suggestions for code improvement or simply quickly understand the architecture of a project & mldr;

  • Legacy code analysis : Give your old code to an LLM to help you understand and modernize it
  • Automated code review : Get a first opinion on your Requests Pull
  • Migration of projects : Facilitate the transition to new technologies by letting AI Analyze the existing structure
  • New onboarding : Allow newcomers to ask relevant questions based on code
  • Intelligent documentation : Generate a first version of technical documentation
  • Safety audits : Facilitate automated analysis of potential vulnerabilities
  • Simplified contribution : Quickly understand a project to be able to contribute
  • Accelerated learning : Analyze open source projects to get good practices

Like that, instead of manually copying the files one by one (what a galley!), GIINGGEST takes care of everything properly for you and you just have to copy paste this in Claude or Chatgpt.

Screenshot 2025 01 21 AT 09 54 39 GIILTGEST

The extension is not content to stupidly transform the code. It also provides you with very useful statistics:

  • The complete structure of files and folders
  • The total size of the extract
  • The number of tokens (crucial to respect the limits of LLM)

This information allows you to optimize your prompts and avoid unpleasant surprises.

To self-hut this thing at home with Docker, first build the image like this:

docker build -t gitingest .

Then run the container:

docker run -d --name gitingest -p 8000:8000 gitingest

The application will then be available at theadresse http://localhost:8000.

It is fast, efficient and respectful of privacy. Like that, no more excuses not to take advantage of the power of AI in your projects!

Discover Gitringest on GitHub

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