GitIngest: Quickly Convert Github Code Repositories to Text Suitable for LLM Understanding

General Introduction

GitIngest is an open source tool designed to transform GitHub code repositories into text suitable for Large Language Model (LLM) hints. With simple operations, users can extract and format the content of any GitHub repository into text suitable for LLM. The tool provides one-click analysis, smart formatting, and statistics to help you quickly get a summary of the structure and content of your repository.GitIngest uses FastAPI as its backend framework and Tailwind CSS to build a clean and responsive user interface.

Experience: https://gitingest.com/

Function List

• One-click analysis: Just paste the GitHub repository URL and get instant results!
• Smart Formatting: Optimized output format for LLM prompts
• Statistical information: Provides file and directory structure, token counting and statistics
• web interface: Simple and responsive user interface, easy to use
• Installation and operation: Supports installing and running via pip and Docker.

Using Help

Easy to use guide

Sample project address: https://github.com/pptt121212/freefluxapi/

github modified to gitingest

https://gitingest.com/pptt121212/freefluxapi/

Installation and Deployment Process

Installation with pip

1. Cloning Warehouse:

   git clone https://github.com/cyclotruc/gitingest.git
cd gitingest

2. Install the dependencies:

   pip install -r requirements.txt

3. Run the application:

   cd src
uvicorn main:app --reload

The application will run on the http://localhost:8000The

Installing with Docker

1. Build the mirror image:

   docker build -t gitingest .

2. Run the container:

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

The application will run on the http://localhost:8000The

Guidelines for use

1. One-click analysis: Open the GitIngest website, paste the URL of your GitHub repository, and click the Analyze button to get a summary of the structure and content of your repository.
2. Smart Formatting: The analysis results will be displayed in an optimized format suitable for direct use in LLM prompts.
3. View Statistics: On the results page, you can view file and directory structures, token counts, and other statistics.
4. web interface: With a simple and responsive user interface, users can easily navigate and manipulate analysis results.

Detailed function operation flow

• Paste URL: Paste the URL of your GitHub repository in the input box.
• click analytics: Click on the Analyze button, wait a few seconds and the system will automatically extract and analyze the contents of the warehouse.
• View Results: The results of the analysis will be displayed on the page, including file and directory structure, text content and statistical information.
• Download summary: Users have the option to download a summary file of the analysis results for easy offline viewing and use.

GitIngest provides powerful features and a clean process that enables users to quickly transform their GitHub codebase into text suitable for LLM prompts, dramatically improving productivity and accuracy.