GoGetGit

GoGetGit is a CLI tool built using the GoFr framework for creating API endpoints. The project scrapes code from a given GitHub repository using the Go-GitHub package, stores code in a vector format using ChromaDB, and processes data with LLaMA 3.2 for natural language understanding. The tool can be run from a terminal with the command gogetgit <GitHub_url>.

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Disclaimer

This is a prototype built in a 24-hr hackathon. The web version will be released shortly and the gogetgit package will be published online to directly download it into your PCs. Many features yet to come.... Feel Free to contribute.

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Features

• GoFr Framework: Used for building endpoints that handle GitHub repository scraping and data processing.
• Go-GitHub: A Go client for GitHub APIs, used for scraping the entire code from a given GitHub repository.
• ChromaDB: A vector storage system used to store and index the code data for quick retrieval.
• LLaMA 3.2: A language model used for processing and understanding the scraped code.
• CLI Tool: A simple terminal command gogetgit <GitHub_url> to initiate the scraping and processing of a GitHub repository.

Requirements

• Go 1.18 or higher
• GoFr framework
• Go-GitHub package
• ChromaDB
• LLaMA 3.2 model (can be integrated via an API or local setup)
• GitHub account (to access repositories)

Installation

1. Clone the repository:

   git clone https://github.com/AnanteshG/GoFr-Hackathon.git

2. Run the Backend LLAMA Server:

   python ollama.py

3. Install dependencies:

   go mod tidy

4. Run the main .go script:

 go run gogetgit.go <GITHUB_URL>

Usage

To use the CLI tool, run the following command in your terminal:

gogetgit <GitHub_url>

Replace <GitHub_url> with the URL of the GitHub repository you want to scrape. The tool will:

1. Clone the repository.
2. Extract all code files.
3. Store code in ChromaDB as vectors.
4. Use LLaMA 3.2 to process the code data (optional, for advanced processing).

How It Works

• GitHub Scraping: The go-github package is used to fetch all files from the specified GitHub repository.
• Vector Storage: Code files are processed into vectors and stored in ChromaDB. This enables fast search and retrieval of code snippets.
• Data Processing with LLaMA 3.2: Once the code is scraped and stored, LLaMA 3.2 is used to analyze and understand the content, allowing for advanced querying or processing based on the repository's codebase.

Contributing

Feel free to fork the repository, make changes, and submit pull requests. Contributions are welcome!

Explanation:

• Project Overview: Describes the overall functionality and components.
• Installation Instructions: Walks through cloning the repo, navigating to it, and installing dependencies.
• Usage: Provides a basic example of how to run the CLI tool.
• How It Works: Explains the internal process, such as using go-github for scraping, ChromaDB for storage, and LLaMA 3.2 for data processing.
• Contributing & License: Common sections that encourage contributions and clarify the license.

This template can be customized further based on any additional details you might want to include!