Dump entire Git repos into a single file for LLM prompts
Hey! I wanted to share a tool I've been working on. It's still very early and a work in progress, but I've found it incredibly helpful when working with Claude and OpenAI's models. What it does: I created a Python script that dumps your entire Git repository into a single file. This makes it much easier to use with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. Key Features: - Respects .gitignore patterns - Generates a tree-like directory structure - Includes file contents for all non-excluded files - Customizable file type filtering Why I find it useful for…
Dump entire Git repos into a single file for LLM prompts launched on September 8, 2024 with 57 votes, #586 of 5,281 launches that month and more than 90% of that year's launches.
In plain words
This Python script converts an entire Git repository into a single file for use with large language models and RAG systems. It respects .gitignore patterns, displays directory structure, includes all file contents, and allows customizable file type filtering. The tool is designed for developers who want to provide LLMs with complete project context for better code suggestions and understanding of implementation details.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey! I wanted to share a tool I've been working on. It's still very early and a work in progress, but I've found it incredibly helpful when working with Claude and OpenAI's models. What it does: I created a Python script that dumps your entire Git repository into a single file. This makes it much easier to use with…
Does a similar job
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I’ve been in the MLOps space for ~10 years, and data is still the hardest unsolved open problem. Code is versioned using Git, data is stored somewhere else, and context often lives in a 3rd location like Slack or GDocs. This is why we built XetHub, a platform that enables teams to treat data like code, using Git. Unlike Git LFS, we don’t just store the files. We use content-defined chunking and Merkle Trees to dedupe against everything in history. This allows small changes in large files to be stored compactly. Read more here:…
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Gitingest is a open-source micro dev-tool that I made over the last week. It turns any public Github repository into a text extract that you can give to your favourite LLM easily. Today I added this url trick to make it even easier to use! How I use it myself: - Quickly generate a README.md boilerplate for a project - Ask LLMs questions about an undocumented codebase It is still very much work in progress and I plan to add many more options (file size limits, exclude patterns..) and a public API I hope this tool can help you Your feedback is very valuable to help me prioritize And…
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- GPGitEase: Python3 CLI to simplify Git usage with LLM-assisted commits2023 · medium.com · ▲14
When working on data science projects I often want to just save my work, without having to think deeply about what’s changed. I found the intentionality of Git to feel like friction in these times, and I built GitEase to simplify my workflow. Instead of having to think about add/commit/push/pull with GitEase I just think about `ge load, ge save, ge share, ge undo`. And for even less thinking, I use an LLM (text-da-vinci-003) to generate commit messages by summarizing the diff. Take a look, try it out, and I’d welcome any contributions & feedback. pip install gitease $ ge —help…
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