Alternatives
Products that do what Version code, models, & datasets together in GitHub does
Hi HN! We just launched a GitHub integration that scales your Git repos to handle 100 terabytes of files in a single repo. XetData enables data scientists and machine learning engineers to version code, models, and datasets together. Most teams have glued together clunky workflows using S3, DVC, Git, Git LFS, and other tools and make true reproducibility difficult: https://news.ycombinator.com/item?id=37694701 We instead embrace and extend Git so end-users don’t need to learn a new tool and a new set of commands. Our implementation is similar to Git LFS, where we take over the…
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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:…
2022 · xethub.com
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Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com
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2018 · github.com
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2017 · quiltdata.com
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Hi everyone! I'm trying to create a version control system that solves some of the problems that Git and other version control software has when working in a team. Let me know if you have any feedback!
2023 · jamsync.dev
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GitDiagram is an open-source micro dev-tool that I made this past week Given any public GitHub repository it generates diagrams in Mermaid.js with Claude 3.5 Sonnet I extract information from the file tree and README for details and interactivity (you can click components to be taken to relevant files and directories) Also, you can replace "hub" with "diagram" in any repository URL to access its diagram I created this because I wanted to contribute to open-source projects but quickly realized their codebases are too massive for me to dig through manually, so this helps me get started I do…
2024 · gitdiagram.com
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Simon(sfarshid) and I spend a lot of time on GitHub. As data nerds we put together a quick tool to explore your repository’s data. How it works: - Data Loading: We use dlt to pull data (issues, PRs, commits, stars) from GitHub - Semantic Layer: Relta wraps the underlying dataset into a semantic layer so the LLM doesn’t hallucinate. - Text-to-SQL: A text-to-SQL agent transforms your plain-English question into a query using the semantic layer - Generative Charts: assistant-ui dynamically generates a chart based on the SQL query - Refinements: If the semantic layer can’t handle your question,…
2024 · github.com
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I was getting tired of copy/pasting reams of code into GPT-4 to give it context before I asked it to help me, so I started this small tool. In a nutshell, gpt-repository-loader will spit out file paths and file contents in a prompt-friendly format. You can also use .gptignore to ignore files/folders that are irrelevant to your prompt. gpt-repository-loader as-is works pretty well in helping me achieve better responses. Eventually, I thought it would be cute to load itself into GPT-4 and have GPT-4 improve it. I was honestly surprised by PR#17. GPT-4 was able to write a valid an…
2023 · github.com
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2014 · github.com
- 13GW
I've always wanted a better way to explore the authorship data embedded in a Git commit log. I'm having fun building a CLI tool to do this. It's a bit like the "Contributors" tab on Github that shows you how many commits each contributor has made but much faster and with many more options. If you get a chance to try it out, please let me know. I'd love to hear feedback and suggestions. Thank you!
2025 · github.com
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2017 · gitorials.com
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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…
2024
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Hey HN, creator of DVC here! DVC (https://dvc.org/) is known as Git for data projects. Technically, DVC codifies your data and machine learning pipelines as text metafiles (with pointers to actual data in S3/GCP/Azure/SSH) while you use Git for the actual versioning. DevOps folks call this approach GitOps or more specifically in this case - DataOps or MLOps. We’ve been working towards 1.0 since we started 3 years ago. What began as my pet project now has 100+ code contributors, 100+ documentation contributors, and thousands of users. Our community has taught us…
2020
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I built this as part of my quest to properly learn data visualization. The code is the easy part! Some lessons learned: - personal verification of the the general truth that pie charts are tough! and the returns are not great for the effort due to people's difficulties perceiving angles - may not use "vanilla" d3 with no React. was difficult to adapt for mobile - the GitHub API provides fairly standardized responses so building dynamic charts wasn't too bad. But when working with streaming data (say Kafka) I can see this getting interesting... schema registry should help but creating a view…
2024 · see-my-repo.netlify.app
- 20LB
Jul 2026 · shipthatcode.com
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2018 · dataturks.com
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2019 · gitlab.com
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2019 · github.com
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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…
2023 · medium.com
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